- AbstractBoxMuller - Class in org.encog.mathutil.randomize.generate
-
Provides the ability for subclasses to generate normally distributed random numbers.
- AbstractBoxMuller() - Constructor for class org.encog.mathutil.randomize.generate.AbstractBoxMuller
-
- AbstractGenerateRandom - Class in org.encog.mathutil.randomize.generate
-
Provides a foundation for most random number generation.
- AbstractGenerateRandom() - Constructor for class org.encog.mathutil.randomize.generate.AbstractGenerateRandom
-
- AbstractGenerator - Class in org.encog.app.generate.generators
-
Abstract class that forms the foundation of most code generators.
- AbstractGenerator() - Constructor for class org.encog.app.generate.generators.AbstractGenerator
-
- AbstractGenomeComparator - Class in org.encog.ml.ea.sort
-
Provides base functionality for comparing genomes.
- AbstractGenomeComparator() - Constructor for class org.encog.ml.ea.sort.AbstractGenomeComparator
-
- AbstractGraphSearch - Class in org.encog.ml.graph.search
-
- AbstractGraphSearch(BasicGraph, BasicNode, SearchGoal) - Constructor for class org.encog.ml.graph.search.AbstractGraphSearch
-
- AbstractPNN - Class in org.encog.neural.pnn
-
Abstract class to build PNN networks upon.
- AbstractPNN(PNNKernelType, PNNOutputMode, int, int) - Constructor for class org.encog.neural.pnn.AbstractPNN
-
Constructor.
- AbstractPrgGenerator - Class in org.encog.ml.prg.generator
-
The abstract base for Full and Grow program generation.
- AbstractPrgGenerator(EncogProgramContext, int) - Constructor for class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Construct the generator.
- AbstractTemplateGenerator - Class in org.encog.app.generate.generators
-
Provides a basic implementation of a template generator.
- AbstractTemplateGenerator() - Constructor for class org.encog.app.generate.generators.AbstractTemplateGenerator
-
- Action - Interface in org.encog.ml.world
-
- ACTION_EAST - Static variable in class org.encog.ml.world.grid.GridWorld
-
- ACTION_NORTH - Static variable in class org.encog.ml.world.grid.GridWorld
-
- ACTION_SOUTH - Static variable in class org.encog.ml.world.grid.GridWorld
-
- ACTION_WEST - Static variable in class org.encog.ml.world.grid.GridWorld
-
- ActionNode - Class in org.encog.ml.schedule
-
- ActionNode(String) - Constructor for class org.encog.ml.schedule.ActionNode
-
- ActionNode(String, double) - Constructor for class org.encog.ml.schedule.ActionNode
-
- actionPerformed(ActionEvent) - Method in class org.encog.platformspecific.j2se.TrainingDialog
-
Called when the user clicks the stop button.
- ActionProbability - Interface in org.encog.ml.world
-
- ACTIVATION_CYCLES - Static variable in class org.encog.persist.PersistConst
-
Snapshot.
- ACTIVATION_FUNCTION - Static variable in class org.encog.persist.PersistConst
-
Activation function.
- ACTIVATION_TYPE - Static variable in class org.encog.persist.PersistConst
-
An activation function.
- ActivationBiPolar - Class in org.encog.engine.network.activation
-
BiPolar activation function.
- ActivationBiPolar() - Constructor for class org.encog.engine.network.activation.ActivationBiPolar
-
Construct the bipolar activation function.
- ActivationBipolarSteepenedSigmoid - Class in org.encog.engine.network.activation
-
The bipolar sigmoid activation function is like the regular sigmoid activation function,
except Bipolar sigmoid activation function.
- ActivationBipolarSteepenedSigmoid() - Constructor for class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
-
- ActivationClippedLinear - Class in org.encog.engine.network.activation
-
Linear activation function that bounds the output to [-1,+1].
- ActivationClippedLinear() - Constructor for class org.encog.engine.network.activation.ActivationClippedLinear
-
- ActivationCompetitive - Class in org.encog.engine.network.activation
-
An activation function that only allows a specified number, usually one, of
the out-bound connection to win.
- ActivationCompetitive() - Constructor for class org.encog.engine.network.activation.ActivationCompetitive
-
Create a competitive activation function with one winner allowed.
- ActivationCompetitive(int) - Constructor for class org.encog.engine.network.activation.ActivationCompetitive
-
Create a competitive activation function with the specified maximum
number of winners.
- ActivationElliott - Class in org.encog.engine.network.activation
-
Computationally efficient alternative to ActivationSigmoid.
- ActivationElliott() - Constructor for class org.encog.engine.network.activation.ActivationElliott
-
Construct a basic HTAN activation function, with a slope of 1.
- ActivationElliottSymmetric - Class in org.encog.engine.network.activation
-
Computationally efficient alternative to ActivationTANH.
- ActivationElliottSymmetric() - Constructor for class org.encog.engine.network.activation.ActivationElliottSymmetric
-
Construct a basic HTAN activation function, with a slope of 1.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationBiPolar
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationClippedLinear
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationCompetitive
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationElliott
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationElliottSymmetric
-
Implements the activation function.
- ActivationFunction - Interface in org.encog.engine.network.activation
-
This interface allows various activation functions to be used with the neural
network.
- activationFunction(double[], int, int) - Method in interface org.encog.engine.network.activation.ActivationFunction
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationGaussian
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationLinear
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationLOG
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationRamp
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationSigmoid
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationSIN
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationSoftMax
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationSteepenedSigmoid
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationStep
-
Implements the activation function.
- activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationTANH
-
Implements the activation function.
- ActivationGaussian - Class in org.encog.engine.network.activation
-
An activation function based on the Gaussian function.
- ActivationGaussian() - Constructor for class org.encog.engine.network.activation.ActivationGaussian
-
- ActivationLinear - Class in org.encog.engine.network.activation
-
The Linear layer is really not an activation function at all.
- ActivationLinear() - Constructor for class org.encog.engine.network.activation.ActivationLinear
-
Construct a linear activation function, with a slope of 1.
- ActivationLOG - Class in org.encog.engine.network.activation
-
An activation function based on the logarithm function.
- ActivationLOG() - Constructor for class org.encog.engine.network.activation.ActivationLOG
-
Construct the activation function.
- ActivationRamp - Class in org.encog.engine.network.activation
-
A ramp activation function.
- ActivationRamp() - Constructor for class org.encog.engine.network.activation.ActivationRamp
-
Default constructor.
- ActivationRamp(double, double, double, double) - Constructor for class org.encog.engine.network.activation.ActivationRamp
-
Construct a ramp activation function.
- ActivationSigmoid - Class in org.encog.engine.network.activation
-
The sigmoid activation function takes on a sigmoidal shape.
- ActivationSigmoid() - Constructor for class org.encog.engine.network.activation.ActivationSigmoid
-
Construct a basic sigmoid function, with a slope of 1.
- ActivationSIN - Class in org.encog.engine.network.activation
-
An activation function based on the sin function, with a double period.
- ActivationSIN() - Constructor for class org.encog.engine.network.activation.ActivationSIN
-
Construct the sin activation function.
- ActivationSoftMax - Class in org.encog.engine.network.activation
-
The softmax activation function.
- ActivationSoftMax() - Constructor for class org.encog.engine.network.activation.ActivationSoftMax
-
Construct the soft-max activation function.
- ActivationSteepenedSigmoid - Class in org.encog.engine.network.activation
-
The Steepened Sigmoid is an activation function typically used with NEAT.
- ActivationSteepenedSigmoid() - Constructor for class org.encog.engine.network.activation.ActivationSteepenedSigmoid
-
Construct a steepend sigmoid activation function.
- ActivationStep - Class in org.encog.engine.network.activation
-
The step activation function is a very simple activation function.
- ActivationStep() - Constructor for class org.encog.engine.network.activation.ActivationStep
-
Create a basic step activation with low=0, center=0, high=1.
- ActivationStep(double, double, double) - Constructor for class org.encog.engine.network.activation.ActivationStep
-
Construct a step activation function.
- ActivationTANH - Class in org.encog.engine.network.activation
-
The hyperbolic tangent activation function takes the curved shape of the
hyperbolic tangent.
- ActivationTANH() - Constructor for class org.encog.engine.network.activation.ActivationTANH
-
Construct a basic HTAN activation function, with a slope of 1.
- ActivationUtil - Class in org.encog.util.obj
-
- ActivationUtil() - Constructor for class org.encog.util.obj.ActivationUtil
-
- AdaBoost - Class in org.encog.ensemble.adaboost
-
- AdaBoost(int, int, EnsembleMLMethodFactory, EnsembleTrainFactory, EnsembleAggregator) - Constructor for class org.encog.ensemble.adaboost.AdaBoost
-
- ADALINEPattern - Class in org.encog.neural.pattern
-
Construct an ADALINE neural network.
- ADALINEPattern() - Constructor for class org.encog.neural.pattern.ADALINEPattern
-
- add(double) - Method in class org.encog.app.quant.util.BarBuffer
-
Add a bar.
- add(double[]) - Method in class org.encog.app.quant.util.BarBuffer
-
Add a bar.
- add(UniverseCell) - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- add(UniverseCell) - Method in interface org.encog.ca.universe.ContinuousCell
-
- add(MLData) - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- add(MLData, MLData) - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- add(MLDataPair) - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- add(int) - Method in class org.encog.mathutil.IntPair
-
- add(int, int) - Method in class org.encog.mathutil.IntPair
-
- add(int, int, double) - Method in class org.encog.mathutil.matrices.Matrix
-
Add a value to one cell in the matrix.
- add(Matrix) - Method in class org.encog.mathutil.matrices.Matrix
-
Add the specified matrix to this matrix.
- add(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Add two matrixes.
- add(RandomVariable) - Method in class org.encog.mathutil.probability.vars.VariableList
-
- add(double[], double[]) - Method in class org.encog.mathutil.VectorAlgebra
-
v1 = v1 + v2
- add(MLData) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- add(MLData, MLData) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- add(MLDataPair) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- add(int, double) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Add a value to the specified index.
- add(int, ComplexNumber) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Add a complex number to the specified index.
- add(int, double) - Method in class org.encog.ml.data.basic.BasicMLData
-
Add a value to the specified index.
- add(MLData) - Method in class org.encog.ml.data.basic.BasicMLDataCentroid
-
Add an element to the centroid.
- add(MLDataPair) - Method in class org.encog.ml.data.basic.BasicMLDataPairCentroid
-
Add an element to the centroid.
- add(MLData) - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
Add a object to the dataset.
- add(MLData, MLData) - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
Add a set of input and ideal data to the dataset.
- add(MLDataPair) - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
Add a an object to the dataset.
- add(MLData) - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
Add a object to the dataset.
- add(MLData, MLData) - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
Add a set of input and ideal data to the dataset.
- add(MLDataPair) - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
Add a an object to the dataset.
- add(MLDataSet) - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
- add(MLData) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Add only input data, for an unsupervised dataset.
- add(MLData, MLData) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Add both the input and ideal data.
- add(MLDataPair) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Add a data pair of both input and ideal data.
- add(MLData) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Not supported.
- add(MLData, MLData) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Not supported.
- add(MLDataPair) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Not supported.
- add(int, ComplexNumber) - Method in interface org.encog.ml.data.MLComplexData
-
Add a complex number to the specified index.
- add(int, double) - Method in interface org.encog.ml.data.MLData
-
Add a value to the specified index.
- add(MLData) - Method in interface org.encog.ml.data.MLDataSet
-
Add a object to the dataset.
- add(MLData, MLData) - Method in interface org.encog.ml.data.MLDataSet
-
Add a set of input and ideal data to the dataset.
- add(MLDataPair) - Method in interface org.encog.ml.data.MLDataSet
-
Add a an object to the dataset.
- add(MLDataSet) - Method in interface org.encog.ml.data.MLSequenceSet
-
Add a new sequence.
- add(int, double) - Method in class org.encog.ml.data.sparse.SparseMLData
-
Add a value to the specified index.
- add(int, double) - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
This will throw an error, as "add" is not supported for bipolar.
- add(MLData) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Adding directly is not supported.
- add(MLData, MLData) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Adding directly is not supported.
- add(MLDataPair) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Adding directly is not supported.
- add(MLData) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
Add a object to the dataset.
- add(MLData, MLData) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
Add a set of input and ideal data to the dataset.
- add(MLDataPair) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
Add a an object to the dataset.
- add(Genome) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Add a genome to this species.
- add(Genome) - Method in interface org.encog.ml.ea.species.Species
-
Add a genome to this species.
- add(BasicPath) - Method in class org.encog.ml.graph.search.FrontierHolder
-
- add(MLData) - Method in class org.encog.ml.kmeans.BasicCluster
-
Add to the cluster.
- add(MLData) - Method in interface org.encog.ml.MLCluster
-
Add data to this cluster.
- add(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform an add on two expression values.
- add(ProgramExtensionTemplate) - Method in enum org.encog.ml.prg.extension.EncogOpcodeRegistry
-
Add an opcode.
- add(FreeformConnection) - Method in class org.encog.neural.freeform.basic.BasicActivationSummation
-
Add an input connection.
- add(FreeformNeuron) - Method in class org.encog.neural.freeform.basic.BasicFreeformLayer
-
Add a neuron to this layer.
- add(FreeformNeuron) - Method in interface org.encog.neural.freeform.FreeformLayer
-
Add a neuron to this layer.
- add(FreeformConnection) - Method in interface org.encog.neural.freeform.InputSummation
-
Add an input connection.
- add(EncogPersistor) - Method in class org.encog.persist.PersistorRegistry
-
Add a persistor.
- add(double[]) - Method in class org.encog.util.arrayutil.VectorWindow
-
Add a single vector to the window.
- add(double[]) - Method in class org.encog.util.arrayutil.WindowDouble
-
Add an array to the window.
- add() - Method in class org.encog.util.datastruct.StackInt
-
- add(int) - Method in class org.encog.util.datastruct.WindowInt
-
- add(double[], double[]) - Static method in class org.encog.util.EngineArray
-
- add(String, File) - Method in class org.encog.util.http.FormUtility
-
Add a file to a multipart form.
- add(String, String) - Method in class org.encog.util.http.FormUtility
-
Add a regular text field to either a regular or multipart form.
- add(O) - Method in interface org.encog.util.kmeans.Centroid
-
Add an element to the centroid.
- add(T) - Method in class org.encog.util.kmeans.Cluster
-
Add a element to the cluster.
- add(double, T) - Method in class org.encog.util.obj.ChooseObject
-
Add an object.
- ADD_NOT_SUPPORTED - Static variable in class org.encog.ml.data.folded.FoldedDataSet
-
Error message: adds are not supported.
- ADD_NOT_SUPPORTED - Static variable in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Error message: adds are not supported.
- addAction(Action) - Method in class org.encog.ml.world.basic.BasicWorld
-
- addAction(Action) - Method in interface org.encog.ml.world.World
-
- addAgent(WorldAgent) - Method in class org.encog.ml.world.basic.BasicWorld
-
- addAgent(WorldAgent) - Method in interface org.encog.ml.world.World
-
- addAllTypes() - Method in class org.encog.ml.prg.extension.ParamTemplate
-
Add all known types.
- addAnalystListener(AnalystListener) - Method in class org.encog.app.analyst.EncogAnalyst
-
Add a listener.
- addArg(double) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Add a double argument.
- addArg(int) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Add an int argument.
- addArg(Object) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Add an object argument.
- addArg(String) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Add a string argument.
- addAttribute(String, String) - Method in class org.encog.parse.tags.write.WriteTags
-
Add an attribute to be written with the next tag.
- addBaseEvent(ParsedEvent) - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
Add a base event.
- addBreak() - Method in class org.encog.app.generate.generators.AbstractGenerator
-
Add a line break;
- addCDATA(String) - Method in class org.encog.parse.tags.write.WriteTags
-
Add CDATA to the output stream.
- addChild(BayesianEvent) - Method in class org.encog.ml.bayesian.BayesianEvent
-
Add a child event.
- addChild(Genome) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Add a child to the next iteration.
- addChild(ActionNode, String, double) - Method in class org.encog.ml.schedule.ScheduleGraph
-
- addChildNodes(TreeNode[]) - Method in class org.encog.ml.tree.basic.BasicTreeNode
-
- addChildNodes(TreeNode[]) - Method in interface org.encog.ml.tree.TreeNode
-
Add child nodes.
- addClass(int) - Method in class org.encog.mathutil.probability.CalcProbability
-
- addColumn(BaseCachedColumn) - Method in class org.encog.app.analyst.csv.basic.BasicCachedFile
-
Add a new column.
- addColumn(float[]) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- addColumn(int, boolean) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Add a column.
- addColumn(boolean) - Method in class org.encog.persist.EncogWriteHelper
-
Add a boolean value as a column.
- addColumn(double) - Method in class org.encog.persist.EncogWriteHelper
-
Add a column as a double.
- addColumn(int) - Method in class org.encog.persist.EncogWriteHelper
-
Add a column as an integer.
- addColumn(String) - Method in class org.encog.persist.EncogWriteHelper
-
Add a column as a string.
- addColumn(ActivationFunction) - Method in class org.encog.persist.EncogWriteHelper
-
- addColumns(List<String>) - Method in class org.encog.persist.EncogWriteHelper
-
Add a list of string columns.
- addCommand(Cmd) - Method in class org.encog.app.analyst.EncogAnalyst
-
Add a command.
- addComment(String) - Method in class org.encog.app.generate.program.EncogTreeNode
-
Add a comment.
- addConstraintRule(ConstraintRule) - Method in class org.encog.ml.ea.rules.BasicRuleHolder
-
Add a constraint rule.
- addConstraintRule(ConstraintRule) - Method in interface org.encog.ml.ea.rules.RuleHolder
-
Add a constraint rule.
- addContent(DocumentRange) - Method in class org.encog.bot.browse.WebPage
-
Add to the content collection.
- addDataUnit(DataUnit) - Method in class org.encog.bot.browse.WebPage
-
Add a data unit to the collection.
- addDescription(TemporalDataDescription) - Method in class org.encog.ml.data.market.MarketMLDataSet
-
Add one description of the type of market data that we are seeking at
each datapoint.
- addDescription(TemporalDataDescription) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Add a data description.
- addElement(DocumentRange) - Method in class org.encog.bot.browse.range.DocumentRange
-
Add an element.
- addExtension(ProgramExtensionTemplate) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Add an opcode to the function factory.
- addExtension(String, int) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Add an opcode to the function factory from the opcode registry.
- addField(OutputFieldGrouped) - Method in class org.encog.util.normalize.output.BasicOutputFieldGroup
-
Add a field to this group.
- addField(OutputFieldGrouped) - Method in interface org.encog.util.normalize.output.OutputFieldGroup
-
Add an output field to the group.
- addFilenameBase(File, String) - Static method in class org.encog.util.file.FileUtil
-
- addGiven(String) - Method in class org.encog.ml.bayesian.bif.BIFDefinition
-
- addGivenEvent(ParsedEvent) - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
- addGoal(State) - Method in class org.encog.ml.world.basic.BasicWorld
-
- addGoal(State) - Method in interface org.encog.ml.world.World
-
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.ADALINEPattern
-
Not used, the ADALINE has no hidden layers, this will throw an error.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.ART1Pattern
-
This will fail, hidden layers are not supported for this type of network.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.BAMPattern
-
Unused, a BAM has no hidden layers.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Not supported, will throw an exception, Boltzmann networks have no hidden
layers.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.CPNPattern
-
Not used, will throw an error.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.ElmanPattern
-
Add a hidden layer with the specified number of neurons.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.FeedForwardPattern
-
Add a hidden layer, with the specified number of neurons.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.HopfieldPattern
-
Add a hidden layer.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.JordanPattern
-
Add a hidden layer, there should be only one.
- addHiddenLayer(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern
-
Add the specified hidden layer.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.PNNPattern
-
Add a hidden layer.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.RadialBasisPattern
-
Add the hidden layer, this should be called once, as a RBF has a single
hidden layer.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.SOMPattern
-
Add a hidden layer.
- addHiddenLayer(int) - Method in class org.encog.neural.pattern.SVMPattern
-
Unused, a BAM has no hidden layers.
- addHiddenLayer(int, int) - Method in class org.encog.neural.prune.PruneIncremental
-
Add a hidden layer's min and max.
- addInclude(String) - Method in class org.encog.app.generate.generators.AbstractGenerator
-
Add an include.
- addInput(FreeformConnection) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Add an input connection to this neuron.
- addInput(FreeformConnection) - Method in interface org.encog.neural.freeform.FreeformNeuron
-
Add an input connection to this neuron.
- addInputField(InputField) - Method in class org.encog.util.normalize.DataNormalization
-
Add an input field.
- addItem(InputField, double) - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
Add a nominal value based on a single value.
- addItem(InputField, double, double) - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
Add a nominal item based on a range.
- addItem(InputField, double) - Method in class org.encog.util.normalize.output.nominal.OutputOneOf
-
Add a nominal value specifying a single value, the high and low values
will be 0.5 below and 0.5 above.
- addItem(InputField, double, double) - Method in class org.encog.util.normalize.output.nominal.OutputOneOf
-
Add a nominal item, specify the low and high values.
- addLayer(Layer) - Method in class org.encog.neural.networks.BasicNetwork
-
Add a layer to the neural network.
- addLine(String) - Method in class org.encog.app.generate.generators.AbstractGenerator
-
Add a line of code, indent proper.
- addLine(String) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Add a line, with proper indention.
- addLine(double, boolean, boolean...) - Method in class org.encog.ml.bayesian.table.BayesianTable
-
Add a new line.
- addLine(double, int, boolean...) - Method in class org.encog.ml.bayesian.table.BayesianTable
-
Add a new line.
- addLine(double, int, int...) - Method in class org.encog.ml.bayesian.table.BayesianTable
-
Add a new line.
- addLine(String) - Method in class org.encog.persist.EncogWriteHelper
-
Add a line.
- addListener(UniverseListener) - Method in class org.encog.ca.runner.BasicCARunner
-
- addListener(UniverseListener) - Method in interface org.encog.ca.runner.CARunner
-
- addMapping(String) - Method in class org.encog.util.normalize.input.InputFieldCSVText
-
Add a string mapping.
- addMember(EnsembleML) - Method in class org.encog.ensemble.adaboost.AdaBoost
-
- addMember(EnsembleML) - Method in class org.encog.ensemble.Ensemble
-
Add a member to the ensemble
- addNameValue(String, double[]) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Add a name value definition, as a double array.
- addNameValue(String, int) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Add a name-value as an int.
- addNameValue(String, int[]) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Add a name-value array where the value is an int array.
- addNameValue(String, String) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Add a name-value where a string is the value.
- addNeuronID(long, List<NEATNeuronGene>, NEATGenome, NEATGenome) - Method in class org.encog.neural.neat.training.opp.NEATCrossover
-
Add a neuron.
- addObjective(double, CalculateScore) - Method in class org.encog.ml.fitness.MultiObjectiveFitness
-
Add an objective.
- addOperation(double, EvolutionaryOperator) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Add an operation.
- addOperation(double, EvolutionaryOperator) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Add an operation.
- addOption(String) - Method in class org.encog.ml.bayesian.bif.BIFVariable
-
- addOutput(FreeformConnection) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Add an output connection to this neuron.
- addOutput(FreeformConnection) - Method in interface org.encog.neural.freeform.FreeformNeuron
-
Add an output connection to this neuron.
- addOutputField(OutputField) - Method in class org.encog.util.normalize.DataNormalization
-
Add an output field.
- addOutputField(OutputField, boolean) - Method in class org.encog.util.normalize.DataNormalization
-
Add a field and allow it to be specified as an "ideal output field".
- addParent(BayesianEvent) - Method in class org.encog.ml.bayesian.BayesianEvent
-
Add a parent event.
- addPattern(MLData, MLData) - Method in class org.encog.neural.bam.BAM
-
Add a pattern to the neural network.
- addPattern(MLData) - Method in class org.encog.neural.thermal.HopfieldNetwork
-
Train the neural network for the specified pattern.
- addPerformer(ConcurrentTrainingPerformer) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Add a performer.
- addPopulationMember(PrgPopulation, EncogProgram) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Add a population member from one of the threads.
- addProperties(Map<String, String>) - Method in class org.encog.persist.EncogWriteHelper
-
Add the specified properties.
- addProperty(String, double) - Method in class org.encog.parse.tags.write.WriteTags
-
Add a property as a double.
- addProperty(String, int) - Method in class org.encog.parse.tags.write.WriteTags
-
Add a property as an integer.
- addProperty(String, String) - Method in class org.encog.parse.tags.write.WriteTags
-
Add a property as a string.
- addProperty(String, double[], int) - Method in class org.encog.parse.tags.write.WriteTags
-
Write an array as a property.
- addProperty(String, int[], int) - Method in class org.encog.parse.tags.write.WriteTags
-
Write an array as a property.
- addRange(double, double, double) - Method in class org.encog.util.normalize.output.mapped.OutputFieldEncode
-
Add a ranged mapped to a value.
- addRange(double, double, boolean) - Method in class org.encog.util.normalize.segregate.RangeSegregator
-
Add a range.
- addRange(SegregationRange) - Method in class org.encog.util.normalize.segregate.RangeSegregator
-
Add a range.
- addRawHeadings(StringBuilder, String, CSVFormat) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Add headings for a raw file.
- Address - Class in org.encog.bot.browse
-
A URL address.
- Address(URL) - Constructor for class org.encog.bot.browse.Address
-
Construct the address from a URL.
- Address(URL, String) - Constructor for class org.encog.bot.browse.Address
-
Construct a URL using a perhaps relative URL and a base URL.
- addRewriteRule(RewriteRule) - Method in class org.encog.ml.ea.rules.BasicRuleHolder
-
Add a rewrite rule.
- addRewriteRule(RewriteRule) - Method in interface org.encog.ml.ea.rules.RuleHolder
-
Add a rewrite rule.
- addRow(int) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Add a row.
- addScoreAdjuster(AdjustScore) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Add a score adjuster.
- addScoreAdjuster(AdjustScore) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Add a score adjuster.
- addSection(String) - Method in class org.encog.persist.EncogWriteHelper
-
Add a new section.
- addSegregator(Segregator) - Method in class org.encog.util.normalize.DataNormalization
-
Add a segregator.
- addShutdownTask(EncogShutdownTask) - Method in class org.encog.Encog
-
Add a shutdown task.
- addSourceColumn(ColumnDefinition) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Add a source column.
- addSpeciesMember(Species, Genome) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
Add a genome.
- addState(State) - Method in class org.encog.ml.world.basic.BasicWorld
-
- addState(State) - Method in interface org.encog.ml.world.World
-
- addStrategy(Strategy) - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Training strategies can be added to improve the training results.
- addStrategy(Strategy) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- addStrategy(Strategy) - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- addStrategy(Strategy) - Method in class org.encog.ml.train.BasicTraining
-
Training strategies can be added to improve the training results.
- addStrategy(Strategy) - Method in interface org.encog.ml.train.MLTrain
-
Training strategies can be added to improve the training results.
- addSubSection(String) - Method in class org.encog.persist.EncogWriteHelper
-
Add a new subsection.
- addTask(AnalystTask) - Method in class org.encog.app.analyst.script.AnalystScript
-
Add a task.
- addTempTraining(int, double) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Add to the specified temp value.
- addTempTraining(int, double) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Add to the specified temp value.
- addTempTraining(int, double) - Method in interface org.encog.neural.freeform.TempTrainingData
-
Add to the specified temp value.
- addText(String) - Method in class org.encog.parse.tags.write.WriteTags
-
Add text.
- addToBeginning(String) - Method in class org.encog.app.generate.generators.AbstractGenerator
-
Add to the beginning of the file.
- addTrainingJob(TrainingJob) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Add a training job.
- addType(String) - Method in class org.encog.ml.prg.extension.ParamTemplate
-
Add the specified type.
- addType(ValueType) - Method in class org.encog.ml.prg.extension.ParamTemplate
-
Add a type using a type enum.
- addWeight(double) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Add to the connection weight.
- addWeight(double) - Method in interface org.encog.neural.freeform.FreeformConnection
-
Add to the connection weight.
- addWeight(int, int, int, double) - Method in class org.encog.neural.networks.BasicNetwork
-
Add to a weight.
- addWeight(int, int, double) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Add to the specified weight.
- addX(int) - Method in class org.encog.mathutil.IntPair
-
- addY(int) - Method in class org.encog.mathutil.IntPair
-
- AdjustScore - Interface in org.encog.ml.ea.score
-
Score adjusters adjust the score according to some means.
- adjustWeights() - Method in class org.encog.neural.art.ART1
-
Adjust the weights for the pattern just presented.
- advance() - Method in class org.encog.util.SimpleParser
-
- advance(int) - Method in class org.encog.util.SimpleParser
-
- AF_BIPOLAR - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_COMPETITIVE - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_GAUSSIAN - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_LINEAR - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_LOG - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_RAMP - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_SIGMOID - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_SIN - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_SOFTMAX - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_SSIGMOID - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_STEP - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AF_TANH - Static variable in class org.encog.ml.factory.MLActivationFactory
-
- AgentPolicy - Interface in org.encog.ml.world
-
- aggregator - Variable in class org.encog.ensemble.Ensemble
-
- aggregatorDataSet - Variable in class org.encog.ensemble.Ensemble
-
- allConstChildren() - Method in class org.encog.ml.prg.ProgramNode
-
- allConstDescendants() - Method in class org.encog.ml.prg.ProgramNode
-
- allLeafChildren() - Method in class org.encog.ml.tree.basic.BasicTreeNode
-
- allLeafChildren() - Method in interface org.encog.ml.tree.TreeNode
-
- allocate(int) - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
Allocate enough space for this column.
- allocateInputVector() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Allocate a data item large enough to hold a single input vector.
- allocateInputVector(int) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Allocate a data item large enough to hold several input vectors.
- allocateMask(int) - Method in class org.encog.ml.data.versatile.division.DataDivision
-
Allocat space to hold the mask.
- allocateTempTraining(int) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Allocate the specified length of temp training.
- allocateTempTraining(int) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Allocate the specified length of temp training.
- allocateTempTraining(int) - Method in interface org.encog.neural.freeform.TempTrainingData
-
Allocate the specified length of temp training.
- alpha - Variable in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Alpha matrix.
- alphaElement(int, int) - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Alpha element.
- AnalystClassItem - Class in org.encog.app.analyst.script
-
Holds a class item for the script.
- AnalystClassItem(String, String, int) - Constructor for class org.encog.app.analyst.script.AnalystClassItem
-
Construct a class item.
- AnalystClusterCSV - Class in org.encog.app.analyst.csv
-
Used by the analyst to cluster a CSV file.
- AnalystClusterCSV() - Constructor for class org.encog.app.analyst.csv.AnalystClusterCSV
-
- AnalystCodeGenerationError - Exception in org.encog.app.generate
-
Analyst code generation error.
- AnalystCodeGenerationError(String) - Constructor for exception org.encog.app.generate.AnalystCodeGenerationError
-
Construct a message exception.
- AnalystCodeGenerationError(String, Throwable) - Constructor for exception org.encog.app.generate.AnalystCodeGenerationError
-
Construct an exception that holds another exception.
- AnalystCodeGenerationError(Throwable) - Constructor for exception org.encog.app.generate.AnalystCodeGenerationError
-
Construct an exception that holds another exception.
- AnalystError - Exception in org.encog.app.analyst
-
An error has occured with the Encog Analyst.
- AnalystError(String) - Constructor for exception org.encog.app.analyst.AnalystError
-
Construct a message exception.
- AnalystError(Throwable) - Constructor for exception org.encog.app.analyst.AnalystError
-
Construct an exception that holds another exception.
- AnalystError(String, Throwable) - Constructor for exception org.encog.app.analyst.AnalystError
-
Construct an exception that holds another exception.
- AnalystEvaluateCSV - Class in org.encog.app.analyst.csv
-
Used by the analyst to evaluate a CSV file.
- AnalystEvaluateCSV() - Constructor for class org.encog.app.analyst.csv.AnalystEvaluateCSV
-
- AnalystEvaluateRawCSV - Class in org.encog.app.analyst.csv
-
Used by the analyst to evaluate a CSV file.
- AnalystEvaluateRawCSV() - Constructor for class org.encog.app.analyst.csv.AnalystEvaluateRawCSV
-
- AnalystField - Class in org.encog.app.analyst.script.normalize
-
Holds a field to be analyzed.
- AnalystField() - Constructor for class org.encog.app.analyst.script.normalize.AnalystField
-
Construct the object with a range of 1 and -1.
- AnalystField(AnalystField) - Constructor for class org.encog.app.analyst.script.normalize.AnalystField
-
Construct an analyst field.
- AnalystField(double, double) - Constructor for class org.encog.app.analyst.script.normalize.AnalystField
-
Construct the object.
- AnalystField(NormalizationAction, String) - Constructor for class org.encog.app.analyst.script.normalize.AnalystField
-
Construct an object.
- AnalystField(NormalizationAction, String, double, double, double, double) - Constructor for class org.encog.app.analyst.script.normalize.AnalystField
-
Construct the field, with no defaults.
- AnalystField(String, NormalizationAction, double, double) - Constructor for class org.encog.app.analyst.script.normalize.AnalystField
-
Construct an analyst field to use.
- AnalystFileFormat - Enum in org.encog.app.analyst
-
CSV file formats used by the Encog Analyst.
- analystFileFormat2String(AnalystFileFormat) - Static method in class org.encog.app.analyst.util.ConvertStringConst
-
Convert a file format to a string.
- AnalystGoal - Enum in org.encog.app.analyst
-
What is the goal of the Encog Analyst?
- AnalystListener - Interface in org.encog.app.analyst
-
Reports the progress of the Encog Analyst.
- AnalystNormalize - Class in org.encog.app.analyst.script.normalize
-
This class holds information about the fields that the Encog Analyst will
normalize.
- AnalystNormalize(AnalystScript) - Constructor for class org.encog.app.analyst.script.normalize.AnalystNormalize
-
Construct the object.
- AnalystNormalizeCSV - Class in org.encog.app.analyst.csv.normalize
-
Normalize, or denormalize, a CSV file.
- AnalystNormalizeCSV() - Constructor for class org.encog.app.analyst.csv.normalize.AnalystNormalizeCSV
-
- AnalystNormalizeToEGB - Class in org.encog.app.analyst.csv.normalize
-
Normalize, or denormalize, a CSV file.
- AnalystNormalizeToEGB() - Constructor for class org.encog.app.analyst.csv.normalize.AnalystNormalizeToEGB
-
- AnalystPreprocess - Class in org.encog.app.analyst.script.preprocess
-
- AnalystPreprocess(AnalystScript) - Constructor for class org.encog.app.analyst.script.preprocess.AnalystPreprocess
-
Construct the object.
- AnalystProcess - Class in org.encog.app.analyst.csv.process
-
Perform many different types of transformations on a CSV.
- AnalystProcess(EncogAnalyst, int, int) - Constructor for class org.encog.app.analyst.csv.process.AnalystProcess
-
Construct the object.
- AnalystProcess - Class in org.encog.app.analyst.script.process
-
Script holder for Encog Analyst preprocessing.
- AnalystProcess() - Constructor for class org.encog.app.analyst.script.process.AnalystProcess
-
- AnalystReport - Class in org.encog.app.analyst.report
-
Produce a simple report on the makeup of the script and data to be analyued.
- AnalystReport(EncogAnalyst) - Constructor for class org.encog.app.analyst.report.AnalystReport
-
Construct the report.
- AnalystReportBridge - Class in org.encog.app.analyst.util
-
Used to bridge the AnalystListerner to an StatusReportable object.
- AnalystReportBridge(EncogAnalyst) - Constructor for class org.encog.app.analyst.util.AnalystReportBridge
-
Construct the bridge object.
- AnalystScript - Class in org.encog.app.analyst.script
-
Holds a script for the Encog Analyst.
- AnalystScript() - Constructor for class org.encog.app.analyst.script.AnalystScript
-
Construct an analyst script.
- AnalystSegregate - Class in org.encog.app.analyst.script.segregate
-
Holds all of the segregation targets for a script.
- AnalystSegregate() - Constructor for class org.encog.app.analyst.script.segregate.AnalystSegregate
-
- AnalystSegregateTarget - Class in org.encog.app.analyst.script.segregate
-
This class specifies a target for the segregation process.
- AnalystSegregateTarget(String, int) - Constructor for class org.encog.app.analyst.script.segregate.AnalystSegregateTarget
-
Construct the segregation target.
- AnalystTask - Class in org.encog.app.analyst.script.task
-
Holds a task in the script.
- AnalystTask(String) - Constructor for class org.encog.app.analyst.script.task.AnalystTask
-
Construct an analyst task.
- AnalystUtility - Class in org.encog.app.analyst.util
-
Provides an interface to the analyst usually used by other programs.
- AnalystUtility(EncogAnalyst) - Constructor for class org.encog.app.analyst.util.AnalystUtility
-
Construct the analyst utility.
- AnalystWizard - Class in org.encog.app.analyst.wizard
-
The Encog Analyst Wizard can be used to create Encog Analyst script files
from a CSV file.
- AnalystWizard(EncogAnalyst) - Constructor for class org.encog.app.analyst.wizard.AnalystWizard
-
Construct the analyst wizard.
- analyze(EncogAnalyst, File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.AnalystClusterCSV
-
Analyze the data.
- analyze(EncogAnalyst, File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.AnalystEvaluateCSV
-
Analyze the data.
- analyze(EncogAnalyst, File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.AnalystEvaluateRawCSV
-
Analyze the data.
- analyze(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.balance.BalanceCSV
-
Analyze the data.
- analyze(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.basic.BasicCachedFile
-
Analyze the input file.
- analyze(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.filter.FilterCSV
-
Analyze the file.
- analyze(File, boolean, CSVFormat, EncogAnalyst) - Method in class org.encog.app.analyst.csv.normalize.AnalystNormalizeCSV
-
Analyze the file.
- analyze(File, boolean, CSVFormat, EncogAnalyst) - Method in class org.encog.app.analyst.csv.normalize.AnalystNormalizeToEGB
-
Analyze the file.
- analyze(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.process.AnalystProcess
-
Analyze the neural network.
- analyze(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.segregate.SegregateCSV
-
Analyze the input file.
- analyze(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.shuffle.ShuffleCSV
-
Analyze the neural network.
- analyze(File, boolean, AnalystFileFormat) - Method in class org.encog.app.analyst.EncogAnalyst
-
Analyze the specified file.
- analyze(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Analyze the specified value.
- analyze(File) - Method in class org.encog.app.analyst.util.AnalystUtility
-
- analyze(String) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
Analyze the specified value.
- analyze() - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Analyze the input and determine max, min, mean, etc.
- analyze(double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Analyze the specified value.
- analyze(double[]) - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
Analyze the 1D array.
- analyze(double[][]) - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
Analyze the 2D array.
- analyze1(String) - Method in class org.encog.app.analyst.analyze.AnalyzedField
-
Perform a pass one analysis of this field.
- analyze2(String) - Method in class org.encog.app.analyst.analyze.AnalyzedField
-
Perform a pass two analysis of this field.
- AnalyzedField - Class in org.encog.app.analyst.analyze
-
This class represents a field that the Encog Analyst is in the process of
analyzing.
- AnalyzedField(AnalystScript, String) - Constructor for class org.encog.app.analyst.analyze.AnalyzedField
-
Construct an analyzed field.
- AnalyzeNetwork - Class in org.encog.neural.networks.structure
-
Allows the weights and bias values of the neural network to be analyzed.
- AnalyzeNetwork(BasicNetwork) - Constructor for class org.encog.neural.networks.structure.AnalyzeNetwork
-
Construct a network analyze class.
- ANNEAL_CYCLES - Static variable in class org.encog.neural.thermal.BoltzmannMachine
-
The property for anneal cycles.
- AnnealFactory - Class in org.encog.ml.factory.train
-
A factory to create simulated annealing trainers.
- AnnealFactory() - Constructor for class org.encog.ml.factory.train.AnnealFactory
-
- appendSeparator(StringBuilder, CSVFormat) - Static method in class org.encog.app.analyst.csv.basic.BasicFile
-
Append a separator.
- applyBonus(double, double) - Method in class org.encog.ml.ea.sort.AbstractGenomeComparator
-
Apply a bonus, this is a simple percent that is applied in the direction
specified by the "should minimize" property of the score function.
- applyBonus(double, double) - Method in interface org.encog.ml.ea.sort.GenomeComparator
-
Apply a bonus, this is a simple percent that is applied in the direction
specified by the "should minimize" property of the score function.
- applyMinMax(double) - Method in class org.encog.util.normalize.input.BasicInputField
-
Given the current value, apply to the min and max values.
- applyMinMax(double) - Method in interface org.encog.util.normalize.input.InputField
-
Update the min and max values for this field with the specified values.
- applyPenalty(double, double) - Method in class org.encog.ml.ea.sort.AbstractGenomeComparator
-
Apply a penalty, this is a simple percent that is applied in the
direction specified by the "should minimize" property of the score
function.
- applyPenalty(double, double) - Method in interface org.encog.ml.ea.sort.GenomeComparator
-
Apply a penalty, this is a simple percent that is applied in the
direction specified by the "should minimize" property of the score
function.
- ArchitectureLayer - Class in org.encog.ml.factory.parse
-
Holds the parse results for one layer.
- ArchitectureLayer() - Constructor for class org.encog.ml.factory.parse.ArchitectureLayer
-
- ArchitectureParse - Class in org.encog.ml.factory.parse
-
This class is used to parse a Encog architecture string.
- arg() - Method in class org.encog.mathutil.ComplexNumber
-
Argument of this Complex number
(the angle in radians with the x-axis in polar coordinates).
- arrayAdd(double[][], double[][]) - Static method in class org.encog.util.EngineArray
-
- arrayCopy(double[]) - Static method in class org.encog.util.EngineArray
-
Copy a double array.
- arrayCopy(byte[]) - Static method in class org.encog.util.EngineArray
-
Copy a byte array.
- arrayCopy(double[], double[]) - Static method in class org.encog.util.EngineArray
-
Completely copy one array into another.
- arrayCopy(double[], float[]) - Static method in class org.encog.util.EngineArray
-
Copy an array of floats to an array of doubles.
- arrayCopy(double[], int, double[], int, int) - Static method in class org.encog.util.EngineArray
-
Copy an array of doubles.
- arrayCopy(double[][]) - Static method in class org.encog.util.EngineArray
-
Copy a 2D double array.
- arrayCopy(float[], double[]) - Static method in class org.encog.util.EngineArray
-
Copy an array of floats to an array of doubles.
- arrayCopy(int[]) - Static method in class org.encog.util.EngineArray
-
Copy an int array.
- arrayCopy(int[], int[]) - Static method in class org.encog.util.EngineArray
-
Completely copy one array into another.
- arrayCopy(byte[], int, byte[], int, int) - Static method in class org.encog.util.EngineArray
-
- arrayCopy(int[], int, int[], int, int) - Static method in class org.encog.util.EngineArray
-
- ArrayDataCODEC - Class in org.encog.ml.data.buffer.codec
-
A CODEC used for arrays.
- ArrayDataCODEC(double[][], double[][]) - Constructor for class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
Construct an array CODEC.
- ArrayDataCODEC() - Constructor for class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
Default constructor.
- ArrayGenome - Interface in org.encog.ml.genetic.genome
-
An array genome represents an array of "something", this allows array
operators such as crossover and mutate to work on the genome.
- arrayToNetwork(double[], MLMethod) - Static method in class org.encog.neural.networks.structure.NetworkCODEC
-
Use an array to populate the memory of the neural network.
- ART - Class in org.encog.neural.art
-
Adaptive Resonance Theory (ART) is a form of neural network developed
by Stephen Grossberg and Gail Carpenter.
- ART() - Constructor for class org.encog.neural.art.ART
-
- ART1 - Class in org.encog.neural.art
-
Implements an ART1 neural network.
- ART1() - Constructor for class org.encog.neural.art.ART1
-
Default constructor, used mainly for persistence.
- ART1(int, int) - Constructor for class org.encog.neural.art.ART1
-
Construct the ART1 network.
- ART1Pattern - Class in org.encog.neural.pattern
-
Pattern to create an ART-1 neural network.
- ART1Pattern() - Constructor for class org.encog.neural.pattern.ART1Pattern
-
- assignGeneID() - Method in class org.encog.neural.neat.NEATPopulation
-
- assignInnovationID() - Method in class org.encog.neural.neat.NEATPopulation
-
- assignInputNormalizer(ColumnType, Normalizer) - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Assign a normalizer to the specified column type for output.
- assignOutputNormalizer(ColumnType, Normalizer) - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Assign a normalizer to the specified column type for output.
- AStarSearch - Class in org.encog.ml.graph.search
-
- AStarSearch(BasicGraph, BasicNode, SearchGoal, CostEstimator) - Constructor for class org.encog.ml.graph.search.AStarSearch
-
- ATanErrorFunction - Class in org.encog.neural.error
-
An ATan based error function.
- ATanErrorFunction() - Constructor for class org.encog.neural.error.ATanErrorFunction
-
- attemptCreateGenome(Random, Population) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Attempt to create a genome.
- autoDecay() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Should be called each iteration if autodecay is desired.
- AutoFloatColumn - Class in org.encog.ml.data.auto
-
- AutoFloatColumn(float[]) - Constructor for class org.encog.ml.data.auto.AutoFloatColumn
-
- AutoFloatColumn(float[], float, float) - Constructor for class org.encog.ml.data.auto.AutoFloatColumn
-
- AutoFloatDataSet - Class in org.encog.ml.data.auto
-
- AutoFloatDataSet(int, int, int, int) - Constructor for class org.encog.ml.data.auto.AutoFloatDataSet
-
- AutoFloatDataSet.AutoFloatIterator - Class in org.encog.ml.data.auto
-
- AutoFloatDataSet.AutoFloatIterator() - Constructor for class org.encog.ml.data.auto.AutoFloatDataSet.AutoFloatIterator
-
- autoMinMax() - Method in class org.encog.ml.data.auto.AutoFloatColumn
-
- average(int) - Method in class org.encog.app.quant.util.BarBuffer
-
Average all of the bars.
- averageGain(int) - Method in class org.encog.app.quant.util.BarBuffer
-
Get the average gain.
- averageLoss(int) - Method in class org.encog.app.quant.util.BarBuffer
-
Get the average loss.
- Averaging - Class in org.encog.ensemble.aggregator
-
- Averaging() - Constructor for class org.encog.ensemble.aggregator.Averaging
-
- Backpropagation - Class in org.encog.neural.networks.training.propagation.back
-
This class implements a backpropagation training algorithm for feed forward
neural networks.
- Backpropagation(ContainsFlat, MLDataSet) - Constructor for class org.encog.neural.networks.training.propagation.back.Backpropagation
-
Create a class to train using backpropagation.
- Backpropagation(ContainsFlat, MLDataSet, double, double) - Constructor for class org.encog.neural.networks.training.propagation.back.Backpropagation
-
- BackpropagationFactory - Class in org.encog.ensemble.training
-
- BackpropagationFactory() - Constructor for class org.encog.ensemble.training.BackpropagationFactory
-
- BackPropFactory - Class in org.encog.ml.factory.train
-
A factory for backpropagation training.
- BackPropFactory() - Constructor for class org.encog.ml.factory.train.BackPropFactory
-
- backward(ActionNode) - Method in class org.encog.ml.schedule.CalculateScheduleTimes
-
- Bagging - Class in org.encog.ensemble.bagging
-
- Bagging(int, int, EnsembleMLMethodFactory, EnsembleTrainFactory, EnsembleAggregator) - Constructor for class org.encog.ensemble.bagging.Bagging
-
- BagOfWords - Class in org.encog.util.text
-
- BagOfWords(int) - Constructor for class org.encog.util.text.BagOfWords
-
- BagOfWords() - Constructor for class org.encog.util.text.BagOfWords
-
- BALANCE_CONFIG_BALANCE_FIELD - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "BALANCE:CONFIG_balanceField".
- BALANCE_CONFIG_COUNT_PER - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "BALANCE:CONFIG_countPer".
- BALANCE_CONFIG_SOURCE_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "BALANCE:CONFIG_sourceFile".
- BALANCE_CONFIG_TARGET_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "BALANCE:CONFIG_targetFile".
- BalanceCSV - Class in org.encog.app.analyst.csv.balance
-
Balance a CSV file.
- BalanceCSV() - Constructor for class org.encog.app.analyst.csv.balance.BalanceCSV
-
- BAM - Class in org.encog.neural.bam
-
Bidirectional associative memory (BAM) is a type of neural network
developed by Bart Kosko in 1988.
- BAM() - Constructor for class org.encog.neural.bam.BAM
-
Default constructor, used mainly for persistence.
- BAM(int, int) - Constructor for class org.encog.neural.bam.BAM
-
Construct the BAM network.
- BAMPattern - Class in org.encog.neural.pattern
-
Construct a Bidirectional Access Memory (BAM) neural network.
- BAMPattern() - Constructor for class org.encog.neural.pattern.BAMPattern
-
- BarBuffer - Class in org.encog.app.quant.util
-
A buffer of bar segments.
- BarBuffer(int) - Constructor for class org.encog.app.quant.util.BarBuffer
-
Construct the object.
- Base64 - Class in org.encog.util.text
-
Encodes and decodes to and from Base64 notation.
- Base64.InputStream - Class in org.encog.util.text
-
A
Base64.InputStream
will read data from another
java.io.InputStream, given in the constructor,
and encode/decode to/from Base64 notation on the fly.
- Base64.InputStream(InputStream) - Constructor for class org.encog.util.text.Base64.InputStream
-
- Base64.InputStream(InputStream, int) - Constructor for class org.encog.util.text.Base64.InputStream
-
- Base64.OutputStream - Class in org.encog.util.text
-
A
Base64.OutputStream
will write data to another
java.io.OutputStream, given in the constructor,
and encode/decode to/from Base64 notation on the fly.
- Base64.OutputStream(OutputStream) - Constructor for class org.encog.util.text.Base64.OutputStream
-
- Base64.OutputStream(OutputStream, int) - Constructor for class org.encog.util.text.Base64.OutputStream
-
- BaseBaumWelch - Class in org.encog.ml.hmm.train.bw
-
This class provides the base implementation for Baum-Welch learning for
HMM's.
- BaseBaumWelch(HiddenMarkovModel, MLSequenceSet) - Constructor for class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- BaseCachedColumn - Class in org.encog.app.analyst.csv.basic
-
A basic cached column.
- BaseCachedColumn(String, boolean, boolean) - Constructor for class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
Construct the cached column.
- BasicAction - Class in org.encog.ml.world.basic
-
- BasicAction(String) - Constructor for class org.encog.ml.world.basic.BasicAction
-
- BasicActivationSummation - Class in org.encog.neural.freeform.basic
-
Provides a basic implementation of an input summation.
- BasicActivationSummation(ActivationFunction) - Constructor for class org.encog.neural.freeform.basic.BasicActivationSummation
-
Construct the activation summation.
- BasicActivationSummationFactory - Class in org.encog.neural.freeform.basic
-
A factory to create BasicFactivationSUmmation objects.
- BasicActivationSummationFactory() - Constructor for class org.encog.neural.freeform.basic.BasicActivationSummationFactory
-
- BasicAgent - Class in org.encog.ml.world.basic
-
- BasicAgent() - Constructor for class org.encog.ml.world.basic.BasicAgent
-
- BasicCachedFile - Class in org.encog.app.analyst.csv.basic
-
Forms the foundation of all of the cached files in Encog Quant.
- BasicCachedFile() - Constructor for class org.encog.app.analyst.csv.basic.BasicCachedFile
-
- BasicCARunner - Class in org.encog.ca.runner
-
- BasicCARunner(Universe, CAProgram) - Constructor for class org.encog.ca.runner.BasicCARunner
-
- BasicCAVisualizer - Class in org.encog.ca.visualize.basic
-
- BasicCAVisualizer(Universe) - Constructor for class org.encog.ca.visualize.basic.BasicCAVisualizer
-
- BasicCellFactory - Class in org.encog.ca.universe.basic
-
- BasicCellFactory(int, double, double) - Constructor for class org.encog.ca.universe.basic.BasicCellFactory
-
- BasicCellFactory(int, int) - Constructor for class org.encog.ca.universe.basic.BasicCellFactory
-
- BasicCluster - Class in org.encog.ml.kmeans
-
Holds a cluster of MLData items that have been clustered
by the KMeansClustering class.
- BasicCluster(Cluster<BasicMLDataPair>) - Constructor for class org.encog.ml.kmeans.BasicCluster
-
Construct a cluster from another.
- BasicContinuousCell - Class in org.encog.ca.universe.basic
-
- BasicContinuousCell(int, double, double) - Constructor for class org.encog.ca.universe.basic.BasicContinuousCell
-
- BasicDiscreteCell - Class in org.encog.ca.universe.basic
-
- BasicDiscreteCell(int, int) - Constructor for class org.encog.ca.universe.basic.BasicDiscreteCell
-
- BasicEA - Class in org.encog.ml.ea.train.basic
-
Provides a basic implementation of a multi-threaded Evolutionary Algorithm.
- BasicEA(Population, CalculateScore) - Constructor for class org.encog.ml.ea.train.basic.BasicEA
-
Construct an EA.
- BasicEdge - Class in org.encog.ml.graph
-
- BasicEdge(BasicNode, BasicNode, double) - Constructor for class org.encog.ml.graph.BasicEdge
-
- BasicFile - Class in org.encog.app.analyst.csv.basic
-
Many of the Encog quant CSV processors are based upon this class.
- BasicFile() - Constructor for class org.encog.app.analyst.csv.basic.BasicFile
-
Construct the object, and set the defaults.
- BasicFreeformConnection - Class in org.encog.neural.freeform.basic
-
A basic freeform connection.
- BasicFreeformConnection(FreeformNeuron, FreeformNeuron) - Constructor for class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Construct a basic freeform connection.
- BasicFreeformConnectionFactory - Class in org.encog.neural.freeform.basic
-
- BasicFreeformConnectionFactory() - Constructor for class org.encog.neural.freeform.basic.BasicFreeformConnectionFactory
-
- BasicFreeformLayer - Class in org.encog.neural.freeform.basic
-
Implements a basic freeform layer.
- BasicFreeformLayer() - Constructor for class org.encog.neural.freeform.basic.BasicFreeformLayer
-
- BasicFreeformLayerFactory - Class in org.encog.neural.freeform.basic
-
A factory that creates BasicFreeformLayer objects.
- BasicFreeformLayerFactory() - Constructor for class org.encog.neural.freeform.basic.BasicFreeformLayerFactory
-
- BasicFreeformNeuron - Class in org.encog.neural.freeform.basic
-
This class provides a basic implementation of a freeform neuron.
- BasicFreeformNeuron(InputSummation) - Constructor for class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
- BasicFreeformNeuronFactory - Class in org.encog.neural.freeform.basic
-
A factory to create BasicFreeformNeuron objects.
- BasicFreeformNeuronFactory() - Constructor for class org.encog.neural.freeform.basic.BasicFreeformNeuronFactory
-
- BasicGenerateID - Class in org.encog.util.identity
-
Used to generate a unique id.
- BasicGenerateID() - Constructor for class org.encog.util.identity.BasicGenerateID
-
Construct the ID generator to start at 1.
- BasicGenerateRandom - Class in org.encog.mathutil.randomize.generate
-
A wrapper over Java's built in random number generator.
- BasicGenerateRandom(long) - Constructor for class org.encog.mathutil.randomize.generate.BasicGenerateRandom
-
Construct a random number generator with the specified seed.
- BasicGenerateRandom() - Constructor for class org.encog.mathutil.randomize.generate.BasicGenerateRandom
-
Construct a random number generator with a time-based seed.
- BasicGenome - Class in org.encog.ml.ea.genome
-
A basic abstract genome.
- BasicGenome() - Constructor for class org.encog.ml.ea.genome.BasicGenome
-
- BasicGraph - Class in org.encog.ml.graph
-
- BasicGraph(BasicNode) - Constructor for class org.encog.ml.graph.BasicGraph
-
- BasicHessian - Class in org.encog.mathutil.matrices.hessian
-
Some basic code used to calculate Hessian matrixes.
- BasicHessian() - Constructor for class org.encog.mathutil.matrices.hessian.BasicHessian
-
- BasicInputField - Class in org.encog.util.normalize.input
-
Provides basic functionality, such as min/max and current value
for other input fields.
- BasicInputField() - Constructor for class org.encog.util.normalize.input.BasicInputField
-
- BasicLayer - Class in org.encog.neural.networks.layers
-
Basic functionality that most of the neural layers require.
- BasicLayer(ActivationFunction, boolean, int) - Constructor for class org.encog.neural.networks.layers.BasicLayer
-
Construct this layer with a non-default activation function, also
determine if a bias is desired or not.
- BasicLayer(int) - Constructor for class org.encog.neural.networks.layers.BasicLayer
-
Construct this layer with a sigmoid activation function.
- BasicML - Class in org.encog.ml
-
A class that provides basic property functionality for the MLProperties
interface.
- BasicML() - Constructor for class org.encog.ml.BasicML
-
- BasicMLComplexData - Class in org.encog.ml.data.basic
-
This class implements a data object that can hold complex numbers.
- BasicMLComplexData(double[]) - Constructor for class org.encog.ml.data.basic.BasicMLComplexData
-
Construct this object with the specified data.
- BasicMLComplexData(ComplexNumber[]) - Constructor for class org.encog.ml.data.basic.BasicMLComplexData
-
Construct this object with the specified data.
- BasicMLComplexData(int) - Constructor for class org.encog.ml.data.basic.BasicMLComplexData
-
Construct this object with blank data and a specified size.
- BasicMLComplexData(MLData) - Constructor for class org.encog.ml.data.basic.BasicMLComplexData
-
Construct a new BasicMLData object from an existing one.
- BasicMLData - Class in org.encog.ml.data.basic
-
Basic implementation of the MLData interface that stores the data in an
array.
- BasicMLData(double[]) - Constructor for class org.encog.ml.data.basic.BasicMLData
-
Construct this object with the specified data.
- BasicMLData(int) - Constructor for class org.encog.ml.data.basic.BasicMLData
-
Construct this object with blank data and a specified size.
- BasicMLData(MLData) - Constructor for class org.encog.ml.data.basic.BasicMLData
-
Construct a new BasicMLData object from an existing one.
- BasicMLDataCentroid - Class in org.encog.ml.data.basic
-
A basic implementation of a centroid.
- BasicMLDataCentroid(MLData) - Constructor for class org.encog.ml.data.basic.BasicMLDataCentroid
-
Construct the centroid.
- BasicMLDataPair - Class in org.encog.ml.data.basic
-
A basic implementation of the MLDataPair interface.
- BasicMLDataPair(MLData) - Constructor for class org.encog.ml.data.basic.BasicMLDataPair
-
Construct the object with only input.
- BasicMLDataPair(MLData, MLData) - Constructor for class org.encog.ml.data.basic.BasicMLDataPair
-
Construct a BasicMLDataPair class with the specified input and ideal
values.
- BasicMLDataPairCentroid - Class in org.encog.ml.data.basic
-
A centroid for BasicMLDataPair.
- BasicMLDataPairCentroid(BasicMLDataPair) - Constructor for class org.encog.ml.data.basic.BasicMLDataPairCentroid
-
Construct the centroid.
- BasicMLDataSet - Class in org.encog.ml.data.basic
-
Stores data in an ArrayList.
- BasicMLDataSet() - Constructor for class org.encog.ml.data.basic.BasicMLDataSet
-
Default constructor.
- BasicMLDataSet(double[][], double[][]) - Constructor for class org.encog.ml.data.basic.BasicMLDataSet
-
Construct a data set from an input and ideal array.
- BasicMLDataSet(List<MLDataPair>) - Constructor for class org.encog.ml.data.basic.BasicMLDataSet
-
Construct a data set from an already created list.
- BasicMLDataSet(MLDataSet) - Constructor for class org.encog.ml.data.basic.BasicMLDataSet
-
Copy whatever dataset type is specified into a memory dataset.
- BasicMLDataSet.BasicMLIterator - Class in org.encog.ml.data.basic
-
An iterator to be used with the BasicMLDataSet.
- BasicMLDataSet.BasicMLIterator() - Constructor for class org.encog.ml.data.basic.BasicMLDataSet.BasicMLIterator
-
- BasicMLSequenceSet - Class in org.encog.ml.data.basic
-
A basic implementation of the MLSequenceSet.
- BasicMLSequenceSet() - Constructor for class org.encog.ml.data.basic.BasicMLSequenceSet
-
Default constructor.
- BasicMLSequenceSet(BasicMLSequenceSet) - Constructor for class org.encog.ml.data.basic.BasicMLSequenceSet
-
- BasicMLSequenceSet(double[][], double[][]) - Constructor for class org.encog.ml.data.basic.BasicMLSequenceSet
-
Construct a data set from an input and ideal array.
- BasicMLSequenceSet(List<MLDataPair>) - Constructor for class org.encog.ml.data.basic.BasicMLSequenceSet
-
Construct a data set from an already created list.
- BasicMLSequenceSet(MLDataSet) - Constructor for class org.encog.ml.data.basic.BasicMLSequenceSet
-
Copy whatever dataset type is specified into a memory dataset.
- BasicMLSequenceSet.BasicMLSeqIterator - Class in org.encog.ml.data.basic
-
An iterator to be used with the BasicMLDataSet.
- BasicMLSequenceSet.BasicMLSeqIterator() - Constructor for class org.encog.ml.data.basic.BasicMLSequenceSet.BasicMLSeqIterator
-
- BasicNetwork - Class in org.encog.neural.networks
-
This class implements a neural network.
- BasicNetwork() - Constructor for class org.encog.neural.networks.BasicNetwork
-
Construct an empty neural network.
- BasicNeuralData - Class in org.encog.neural.data.basic
-
This is an alias class for Encog 2.5 compatibility.
- BasicNeuralData(double[]) - Constructor for class org.encog.neural.data.basic.BasicNeuralData
-
Construct from a double array.
- BasicNeuralData(int) - Constructor for class org.encog.neural.data.basic.BasicNeuralData
-
Construct to a specific size.
- BasicNeuralData(NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralData
-
Construct from another object.
- BasicNeuralDataPair - Class in org.encog.neural.data.basic
-
This is an alias class for Encog 2.5 compatibility.
- BasicNeuralDataPair(NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataPair
-
Construct with input only.
- BasicNeuralDataPair(NeuralData, NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataPair
-
Construct from input and ideal.
- BasicNeuralDataSet - Class in org.encog.neural.data.basic
-
This is an alias class for Encog 2.5 compatibility.
- BasicNeuralDataSet() - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet
-
Construct empty.
- BasicNeuralDataSet(double[][], double[][]) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet
-
Construct from 2d arrays.
- BasicNeuralDataSet(List<MLDataPair>) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet
-
Construct from another list.
- BasicNeuralDataSet(NeuralDataSet) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet
-
Construct from another object.
- BasicNode - Class in org.encog.ml.graph
-
- BasicNode(String) - Constructor for class org.encog.ml.graph.BasicNode
-
- BasicNormalizationStrategy - Class in org.encog.ml.data.versatile.normalizers.strategies
-
Provides a basic normalization strategy that will work with most models built into Encog.
- BasicNormalizationStrategy(double, double, double, double) - Constructor for class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Construct the basic normalization strategy.
- BasicNormalizationStrategy() - Constructor for class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Default constructor.
- BasicOutputField - Class in org.encog.util.normalize.output
-
Provides very basic functionality for output fields.
- BasicOutputField() - Constructor for class org.encog.util.normalize.output.BasicOutputField
-
- BasicOutputFieldGroup - Class in org.encog.util.normalize.output
-
Provides very basic functionality that other output field groups
will use.
- BasicOutputFieldGroup() - Constructor for class org.encog.util.normalize.output.BasicOutputFieldGroup
-
- BasicPath - Class in org.encog.ml.graph
-
- BasicPath(BasicNode) - Constructor for class org.encog.ml.graph.BasicPath
-
- BasicPath(BasicPath, BasicNode) - Constructor for class org.encog.ml.graph.BasicPath
-
- BasicPNN - Class in org.encog.neural.pnn
-
This class implements either a:
Probabilistic Neural Network (PNN)
General Regression Neural Network (GRNN)
To use a PNN specify an output mode of classification, to make use of a GRNN
specify either an output mode of regression or un-supervised autoassociation.
- BasicPNN(PNNKernelType, PNNOutputMode, int, int) - Constructor for class org.encog.neural.pnn.BasicPNN
-
Construct a BasicPNN network.
- BasicPopulation - Class in org.encog.ml.ea.population
-
Defines the basic functionality for a population of genomes.
- BasicPopulation() - Constructor for class org.encog.ml.ea.population.BasicPopulation
-
Construct an empty population.
- BasicPopulation(int, GenomeFactory) - Constructor for class org.encog.ml.ea.population.BasicPopulation
-
Construct a population.
- BasicProgram - Class in org.encog.ca.program.basic
-
- BasicProgram(Movement[]) - Constructor for class org.encog.ca.program.basic.BasicProgram
-
- BasicQuery - Class in org.encog.ml.bayesian.query
-
Provides basic functionality for a Bayesian query.
- BasicQuery() - Constructor for class org.encog.ml.bayesian.query.BasicQuery
-
Default constructor.
- BasicQuery(BayesianNetwork) - Constructor for class org.encog.ml.bayesian.query.BasicQuery
-
- BasicRandomFactory - Class in org.encog.mathutil.randomize.factory
-
Basic random number generator factory.
- BasicRandomFactory() - Constructor for class org.encog.mathutil.randomize.factory.BasicRandomFactory
-
Construct a random generator factory.
- BasicRandomFactory(long) - Constructor for class org.encog.mathutil.randomize.factory.BasicRandomFactory
-
Construct a random generator factory with the specified seed.
- BasicRandomizer - Class in org.encog.mathutil.randomize
-
Provides basic functionality that most randomizers will need.
- BasicRandomizer() - Constructor for class org.encog.mathutil.randomize.BasicRandomizer
-
Construct a random number generator with a random(current time) seed.
- BasicRBF - Class in org.encog.mathutil.rbf
-
Basic radial basis function.
- BasicRBF() - Constructor for class org.encog.mathutil.rbf.BasicRBF
-
- BasicRuleHolder - Class in org.encog.ml.ea.rules
-
Basic implementation of a rule holder.
- BasicRuleHolder() - Constructor for class org.encog.ml.ea.rules.BasicRuleHolder
-
- BasicSpecies - Class in org.encog.ml.ea.species
-
Provides basic functionality for a species.
- BasicSpecies() - Constructor for class org.encog.ml.ea.species.BasicSpecies
-
Default constructor, used mainly for persistence.
- BasicSpecies(Population, Genome) - Constructor for class org.encog.ml.ea.species.BasicSpecies
-
Construct a species.
- BasicState - Class in org.encog.ml.world.basic
-
- BasicState() - Constructor for class org.encog.ml.world.basic.BasicState
-
- BasicTemplate - Class in org.encog.ml.prg.extension
-
A basic template.
- BasicTemplate(int, String, NodeType, boolean, int) - Constructor for class org.encog.ml.prg.extension.BasicTemplate
-
Construct a basic template object.
- BasicTemplate(String) - Constructor for class org.encog.ml.prg.extension.BasicTemplate
-
Construct a function based on the provided signature.
- BasicTraining - Class in org.encog.ml.train
-
An abstract class that implements basic training for most training
algorithms.
- BasicTraining() - Constructor for class org.encog.ml.train.BasicTraining
-
Used for serialization.
- BasicTraining(TrainingImplementationType) - Constructor for class org.encog.ml.train.BasicTraining
-
- BasicTrainSOM - Class in org.encog.neural.som.training.basic
-
This class implements competitive training, which would be used in a
winner-take-all neural network, such as the self organizing map (SOM).
- BasicTrainSOM(SOM, double, MLDataSet, NeighborhoodFunction) - Constructor for class org.encog.neural.som.training.basic.BasicTrainSOM
-
Create an instance of competitive training.
- BasicTreeNode - Class in org.encog.ml.tree.basic
-
- BasicTreeNode() - Constructor for class org.encog.ml.tree.basic.BasicTreeNode
-
- BasicUniverse - Class in org.encog.ca.universe.basic
-
- BasicUniverse(int, int, UniverseCellFactory) - Constructor for class org.encog.ca.universe.basic.BasicUniverse
-
- BasicWorld - Class in org.encog.ml.world.basic
-
- BasicWorld() - Constructor for class org.encog.ml.world.basic.BasicWorld
-
- BatchSize - Interface in org.encog.neural.networks.training
-
The batch size.
- BayesEstimator - Interface in org.encog.ml.bayesian.training.estimator
-
An estimator is used during Bayesian training to determine optimal probability values.
- BayesianChoice - Class in org.encog.ml.bayesian
-
A choice in a Bayesian network.
- BayesianChoice(String, double, double) - Constructor for class org.encog.ml.bayesian.BayesianChoice
-
Construct a continuous choice that covers the specified range.
- BayesianChoice(String, int) - Constructor for class org.encog.ml.bayesian.BayesianChoice
-
Construct a discrete choice for the specified index.
- BayesianError - Exception in org.encog.ml.bayesian
-
Thrown when an error occurs working with Bayesian networks.
- BayesianError(String) - Constructor for exception org.encog.ml.bayesian.BayesianError
-
Construct a message exception.
- BayesianError(Throwable) - Constructor for exception org.encog.ml.bayesian.BayesianError
-
Construct an exception that holds another exception.
- BayesianError(String, Throwable) - Constructor for exception org.encog.ml.bayesian.BayesianError
-
Construct an exception that holds another exception.
- BayesianEvent - Class in org.encog.ml.bayesian
-
Events make up a Bayesian network.
- BayesianEvent(String, List<BayesianChoice>) - Constructor for class org.encog.ml.bayesian.BayesianEvent
-
Construct an event with the specified label and choices.
- BayesianEvent(String, String[]) - Constructor for class org.encog.ml.bayesian.BayesianEvent
-
Construct an event with the specified label and choices.
- BayesianEvent(String) - Constructor for class org.encog.ml.bayesian.BayesianEvent
-
Construct a boolean event.
- BayesianFactory - Class in org.encog.ml.factory.method
-
Factory to create bayesian networks.
- BayesianFactory() - Constructor for class org.encog.ml.factory.method.BayesianFactory
-
- BayesianInit - Enum in org.encog.ml.bayesian.training
-
The method by which a Bayesian network should be initialized.
- BayesianNetwork - Class in org.encog.ml.bayesian
-
The Bayesian Network is a machine learning method that is based on
probability, and particularly Bayes' Rule.
- BayesianNetwork() - Constructor for class org.encog.ml.bayesian.BayesianNetwork
-
- BayesianQuery - Interface in org.encog.ml.bayesian.query
-
A Bayesian query.
- BayesianTable - Class in org.encog.ml.bayesian.table
-
Holds a Bayesian truth table.
- BayesianTable(BayesianEvent) - Constructor for class org.encog.ml.bayesian.table.BayesianTable
-
- BayesSearch - Interface in org.encog.ml.bayesian.training.search.k2
-
Search for a good Bayes structure.
- beginBar(Date) - Method in class org.encog.app.quant.ninja.NinjaStreamWriter
-
Begin a bar, for the specified date/time.
- beginBody() - Method in class org.encog.util.HTMLReport
-
- beginDocument() - Method in class org.encog.parse.tags.write.WriteTags
-
Called to begin the document.
- beginHTML() - Method in class org.encog.util.HTMLReport
-
- beginList() - Method in class org.encog.util.HTMLReport
-
- beginLoad(int, int) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Begin loading to the binary file.
- beginPara() - Method in class org.encog.util.HTMLReport
-
- beginRow() - Method in class org.encog.util.HTMLReport
-
- beginRow() - Method in class org.encog.util.normalize.output.nominal.NominalItem
-
Begin a row.
- beginTable() - Method in class org.encog.util.HTMLReport
-
- beginTableInCell(int) - Method in class org.encog.util.HTMLReport
-
- beginTag(String) - Method in class org.encog.parse.tags.write.WriteTags
-
Begin a tag with the specified name.
- BestClose - Class in org.encog.app.quant.indicators.predictive
-
Get the best close.
- BestClose(int, boolean) - Constructor for class org.encog.app.quant.indicators.predictive.BestClose
-
Construct the object.
- BestMatchingUnit - Class in org.encog.neural.som.training.basic
-
The "Best Matching Unit" or BMU is a very important concept in the training
for a SOM.
- BestMatchingUnit(SOM) - Constructor for class org.encog.neural.som.training.basic.BestMatchingUnit
-
Construct a BestMatchingUnit class.
- BestReturn - Class in org.encog.app.quant.indicators.predictive
-
Get the best return.
- BestReturn(int, boolean) - Constructor for class org.encog.app.quant.indicators.predictive.BestReturn
-
Construct the object.
- beta - Variable in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Beta matrix.
- betaElement(int, int) - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Beta element, best element.
- BIFDefinition - Class in org.encog.ml.bayesian.bif
-
Holds a BIF definition.
- BIFDefinition() - Constructor for class org.encog.ml.bayesian.bif.BIFDefinition
-
- BIFHandler - Class in org.encog.ml.bayesian.bif
-
Handler, used to parse the XML BIF files.
- BIFHandler() - Constructor for class org.encog.ml.bayesian.bif.BIFHandler
-
Constructor.
- BIFUtil - Class in org.encog.ml.bayesian.bif
-
A utility class to read and write Bayesian networks in BIF format.
- BIFUtil() - Constructor for class org.encog.ml.bayesian.bif.BIFUtil
-
- BIFVariable - Class in org.encog.ml.bayesian.bif
-
A BIF variable.
- BIFVariable() - Constructor for class org.encog.ml.bayesian.bif.BIFVariable
-
- binary2External(File) - Method in class org.encog.ml.data.buffer.BinaryDataLoader
-
Convert an Encog binary file to an external form, such as CSV.
- BinaryDataLoader - Class in org.encog.ml.data.buffer
-
This class is used, together with a CODEC, to move data to/from the Encog
binary training file format.
- BinaryDataLoader(DataSetCODEC) - Constructor for class org.encog.ml.data.buffer.BinaryDataLoader
-
Construct a loader with the specified CODEC.
- bipolar2double(boolean) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert a boolean to a bipolar number.
- bipolar2double(boolean[]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert a boolean array to a bipolar array.
- bipolar2double(boolean[][]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
- BiPolarNeuralData - Class in org.encog.ml.data.specific
-
A NeuralData implementation designed to work with bipolar data.
- BiPolarNeuralData(boolean[]) - Constructor for class org.encog.ml.data.specific.BiPolarNeuralData
-
Construct this object with the specified data.
- BiPolarNeuralData(int) - Constructor for class org.encog.ml.data.specific.BiPolarNeuralData
-
Construct a data object with the specified size.
- BiPolarUtil - Class in org.encog.mathutil.matrices
-
This class contains a number of utility methods used to work with bipolar
numbers.
- bold(String) - Method in class org.encog.util.HTMLReport
-
- BoltzmannMachine - Class in org.encog.neural.thermal
-
Implements a Boltzmann machine.
- BoltzmannMachine() - Constructor for class org.encog.neural.thermal.BoltzmannMachine
-
Default constructors.
- BoltzmannMachine(int) - Constructor for class org.encog.neural.thermal.BoltzmannMachine
-
Construct a Boltzmann machine with the specified number of neurons.
- BoltzmannPattern - Class in org.encog.neural.pattern
-
Pattern to create a Boltzmann machine.
- BoltzmannPattern() - Constructor for class org.encog.neural.pattern.BoltzmannPattern
-
- BotError - Exception in org.encog.bot
-
Used to represent any error that occurs in the bot part of Encog.
- BotError(String) - Constructor for exception org.encog.bot.BotError
-
Construct a message exception.
- BotError(Throwable) - Constructor for exception org.encog.bot.BotError
-
Construct an exception that holds another exception.
- BotUtil - Class in org.encog.bot
-
Utility class for bots.
- bound(double) - Static method in class org.encog.mathutil.BoundNumbers
-
Bound the number so that it does not become too big or too small.
- BoundMath - Class in org.encog.mathutil
-
Java will sometimes return Math.NaN or Math.Infinity when numbers get to
large or too small.
- BoundNumbers - Class in org.encog.mathutil
-
A simple class that prevents numbers from getting either too big or too
small.
- boxMuller(double, double) - Method in class org.encog.mathutil.randomize.GaussianRandomizer
-
Compute a Gaussian random number.
- BPROPJob - Class in org.encog.neural.networks.training.concurrent.jobs
-
A training definition for BPROP training.
- BPROPJob(BasicNetwork, MLDataSet, boolean, double, double) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
-
Construct a job definition for RPROP.
- BreadthFirstSearch - Class in org.encog.ml.graph.search
-
- BreadthFirstSearch(BasicGraph, BasicNode, SearchGoal) - Constructor for class org.encog.ml.graph.search.BreadthFirstSearch
-
- brentmin(int, double, double, double, CalculationCriteria, double) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
Use the "Brent Method" to find a better minimum.
- BrowseError - Exception in org.encog.bot.browse
-
Thrown when any sort of error related to web browsing is encountered.
- BrowseError(String) - Constructor for exception org.encog.bot.browse.BrowseError
-
Construct a message exception.
- BrowseError(Throwable) - Constructor for exception org.encog.bot.browse.BrowseError
-
Construct an exception that holds another exception.
- Browser - Class in org.encog.bot.browse
-
The main class for web browsing.
- Browser() - Constructor for class org.encog.bot.browse.Browser
-
- BUFFER_SIZE - Static variable in class org.encog.bot.BotUtil
-
How much data to read at once.
- BUFFER_SIZE - Static variable in class org.encog.util.file.Directory
-
Default buffer size for read/write operations.
- BUFFER_SIZE - Static variable in class org.encog.util.http.FormUtility
-
The size of the read buffer.
- BufferedDataError - Exception in org.encog.ml.data.buffer
-
An error occurs working with the Encog binary training format.
- BufferedDataError(String) - Constructor for exception org.encog.ml.data.buffer.BufferedDataError
-
Construct a message exception.
- BufferedDataError(Throwable) - Constructor for exception org.encog.ml.data.buffer.BufferedDataError
-
Construct an exception that holds another exception.
- BufferedDataError(String, Throwable) - Constructor for exception org.encog.ml.data.buffer.BufferedDataError
-
Construct an exception that holds another exception.
- BufferedDataSetIterator - Class in org.encog.ml.data.buffer
-
An iterator for the BufferedNeuralDataSet.
- BufferedDataSetIterator(BufferedMLDataSet) - Constructor for class org.encog.ml.data.buffer.BufferedDataSetIterator
-
Construct the iterator.
- BufferedMLDataSet - Class in org.encog.ml.data.buffer
-
This class is not memory based, so very long files can be used, without
running out of memory.
- BufferedMLDataSet(File) - Constructor for class org.encog.ml.data.buffer.BufferedMLDataSet
-
Construct the dataset using the specified binary file.
- buildCPPNActivationFunctions(ChooseObject<ActivationFunction>) - Static method in class org.encog.neural.hyperneat.HyperNEATGenome
-
Build the CPPN activation functions.
- buildForNetworkInput(double[]) - Method in class org.encog.util.normalize.DataNormalization
-
Build "input data for a neural network" based on the input values
provided.
- C - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- C_SVC - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- cache_size - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- calcErrorWithMultipleSigma(double[], double[], double[], boolean) - Method in interface org.encog.neural.networks.training.pnn.CalculationCriteria
-
Calculate the error with multiple sigmas.
- calcErrorWithMultipleSigma(double[], double[], double[], boolean) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Calculate the error with multiple sigmas.
- calcErrorWithSingleSigma(double) - Method in interface org.encog.neural.networks.training.pnn.CalculationCriteria
-
Calculate the error with a single sigma.
- calcErrorWithSingleSigma(double) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Calculate the error using a common sigma.
- CalcProbability - Class in org.encog.mathutil.probability
-
- CalcProbability(int) - Constructor for class org.encog.mathutil.probability.CalcProbability
-
- CalcProbability() - Constructor for class org.encog.mathutil.probability.CalcProbability
-
- calculate(Map<String, BaseCachedColumn>, int) - Method in class org.encog.app.quant.indicators.Indicator
-
Calculate this indicator.
- calculate(Map<String, BaseCachedColumn>, int) - Method in class org.encog.app.quant.indicators.MovingAverage
-
Calculate this indicator.
- calculate(Map<String, BaseCachedColumn>, int) - Method in class org.encog.app.quant.indicators.predictive.BestClose
-
Calculate the indicator.
- calculate(Map<String, BaseCachedColumn>, int) - Method in class org.encog.app.quant.indicators.predictive.BestReturn
-
Calculate the indicator.
- calculate(UniverseCell) - Method in class org.encog.ca.program.generic.Trans
-
- calculate() - Method in class org.encog.mathutil.error.ErrorCalculation
-
Returns the root mean square error for a complete training set.
- calculate(int) - Method in class org.encog.mathutil.probability.CalcProbability
-
- calculate(double[]) - Method in class org.encog.mathutil.rbf.GaussianFunction
-
Calculate the result from the function.
- calculate(double[]) - Method in class org.encog.mathutil.rbf.InverseMultiquadricFunction
-
Calculate the RBF result for the specified value.
- calculate(double[]) - Method in class org.encog.mathutil.rbf.MexicanHatFunction
-
Calculate the result from the function.
- calculate(double[]) - Method in class org.encog.mathutil.rbf.MultiquadricFunction
-
Calculate the RBF result for the specified value.
- calculate(double[]) - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
Calculate the RBF result for the specified value.
- calculate(ScheduleGraph) - Method in class org.encog.ml.schedule.CalculateScheduleTimes
-
- calculate(State, State, Action) - Method in interface org.encog.ml.world.ActionProbability
-
- calculate(State, State, Action) - Method in class org.encog.ml.world.grid.probability.GridDeterministicProbability
-
- calculate(State, State, Action) - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- calculate() - Method in class org.encog.neural.freeform.basic.BasicActivationSummation
-
Perform the summation, and apply the activation function.
- calculate() - Method in interface org.encog.neural.freeform.InputSummation
-
Perform the summation, and apply the activation function.
- calculate(int, double, double, double, CalculationCriteria, int, double[], double, double[], double[], double[], double[], double[]) - Method in class org.encog.neural.networks.training.pnn.DeriveMinimum
-
Derive the minimum, using a conjugate gradient method.
- calculate(int) - Method in class org.encog.util.normalize.output.mapped.OutputFieldEncode
-
Calculate the value for this field.
- calculate(int) - Method in class org.encog.util.normalize.output.multiplicative.OutputFieldMultiplicative
-
Calculate the value for this output field.
- calculate(int) - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
Calculate the value for the specified subfield.
- calculate(int) - Method in class org.encog.util.normalize.output.nominal.OutputOneOf
-
Calculate the value for the specified subfield.
- calculate(int) - Method in interface org.encog.util.normalize.output.OutputField
-
Calculate the value for this field.
- calculate(int) - Method in class org.encog.util.normalize.output.OutputFieldDirect
-
Calculate the value for this field.
- calculate(double, double, double, double, double) - Static method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
Calculate a ranged mapped value.
- calculate(int) - Method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
Calculate this output field.
- calculate(int) - Method in class org.encog.util.normalize.output.zaxis.OutputFieldZAxis
-
Calculate the current value for this field.
- calculate(int) - Method in class org.encog.util.normalize.output.zaxis.OutputFieldZAxisSynthetic
-
Calculate the synthetic value for this Z-Axis normalization.
- calculateActualSetSize() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Calculate the actual set size, this is the number of training set entries
that will be generated.
- calculateAdjustment(Genome) - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
Calculate the score adjustment.
- calculateAdjustment(Genome) - Method in interface org.encog.ml.ea.score.AdjustScore
-
Calculate the score adjustment.
- calculateBMU(MLData) - Method in class org.encog.neural.som.training.basic.BestMatchingUnit
-
Calculate the best matching unit (BMU).
- calculateClassificationError(MLClassification, MLDataSet) - Static method in class org.encog.util.simple.EncogUtility
-
Calculate the classification error.
- calculateEnergy() - Method in class org.encog.neural.thermal.ThermalNetwork
-
- calculateError(MLDataSet) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Calculate the error of the ML method, given a dataset.
- calculateError(MLDataSet) - Method in class org.encog.ml.fitting.linear.LinearRegression
-
- calculateError(MLDataSet) - Method in interface org.encog.ml.MLError
-
Calculate the error of the ML method, given a dataset.
- calculateError(MLMethod, MLDataSet) - Method in class org.encog.ml.model.EncogModel
-
Calculate the error for the given method and dataset.
- calculateError(MLDataSet) - Method in class org.encog.ml.prg.EncogProgram
-
Calculate the error of the ML method, given a dataset.
- calculateError(MLDataSet) - Method in class org.encog.ml.svm.SVM
-
Calculate the error for this SVM.
- calculateError(MLDataSet) - Method in class org.encog.neural.cpn.CPN
-
Calculate the error for this neural network.
- calculateError(double[], double[], double[]) - Method in class org.encog.neural.error.ATanErrorFunction
-
Calculate the error.
- calculateError(double[], double[], double[]) - Method in interface org.encog.neural.error.ErrorFunction
-
Calculate the error.
- calculateError(double[], double[], double[]) - Method in class org.encog.neural.error.LinearErrorFunction
-
Calculate the error.
- calculateError(double[], double[], double[]) - Method in class org.encog.neural.error.OutputErrorFunction
-
- calculateError(MLDataSet) - Method in class org.encog.neural.flat.FlatNetwork
-
Calculate the error for this neural network.
- calculateError(MLDataSet) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Calculate the error of the ML method, given a dataset.
- calculateError(MLDataSet) - Method in class org.encog.neural.neat.NEATNetwork
-
Calculate the error for this neural network.
- calculateError(MLDataSet) - Method in class org.encog.neural.neat.NEATPopulation
-
Calculate the error of the ML method, given a dataset.
- calculateError(MLDataSet) - Method in class org.encog.neural.networks.BasicNetwork
-
Calculate the error for this neural network.
- calculateError(MLDataSet, boolean) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Calculate the error for the entire training set.
- calculateError(MLDataSet) - Method in class org.encog.neural.pnn.BasicPNN
-
Calculate the error of the ML method, given a dataset.
- calculateError(MLDataSet) - Method in class org.encog.neural.rbf.RBFNetwork
-
Calculate the error for this neural network.
- calculateError(MLDataSet) - Method in class org.encog.neural.som.SOM
-
Calculate the error of the ML method, given a dataset.
- calculateError(MLRegression, MLDataSet) - Static method in class org.encog.util.error.CalculateRegressionError
-
- calculateESS() - Method in class org.encog.mathutil.error.ErrorCalculation
-
Calculate the error with SSE.
- calculateEuclideanDistance(Matrix, MLData, int) - Method in class org.encog.neural.som.training.basic.BestMatchingUnit
-
Calculate the Euclidean distance for the specified output neuron and the
input vector.
- calculateG(BayesianNetwork, BayesianEvent, List<BayesianEvent>) - Method in class org.encog.ml.bayesian.training.search.k2.SearchK2
-
Calculate G.
- calculateGradients() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Calculate the gradients.
- calculateGradients() - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
Calculate the gradients.
- calculateInputColumns() - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
-
- calculateLowerStep(DimensionConstraint, int) - Method in class org.encog.mathutil.dimension.MultiDimension
-
- calculateMax(int, int) - Method in class org.encog.util.arrayutil.WindowDouble
-
Calculate the max value, for the specified index, over all of the data in
the window.
- calculateMin(int, int) - Method in class org.encog.util.arrayutil.WindowDouble
-
Calculate the max value, for the specified index, over all of the data in
the window.
- calculateMSE() - Method in class org.encog.mathutil.error.ErrorCalculation
-
Calculate the error with MSE.
- calculateN(BayesianNetwork, BayesianEvent, List<BayesianEvent>, int[], int) - Method in class org.encog.ml.bayesian.training.search.k2.SearchK2
-
Calculate the value N, which is the number of cases, from the training data, where the
desiredValue matches the training data.
- calculateN(BayesianNetwork, BayesianEvent, List<BayesianEvent>, int[]) - Method in class org.encog.ml.bayesian.training.search.k2.SearchK2
-
Calculate the value N, which is the number of cases, from the training data, where the
desiredValue matches the training data.
- calculateNeuronCount() - Method in class org.encog.neural.networks.BasicNetwork
-
Calculate the total number of neurons in the network across all layers.
- calculateNeuronCounts() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Calculate how many input and output neurons will be needed for the
current data.
- calculateNormalizedInputCount() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- calculateNormalizedOutputCount() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- calculateOutputColumns() - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
-
Calculate the output columns.
- calculateParameterCount() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- calculateParameterCount() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- calculatePathCost(BasicPath) - Method in class org.encog.ml.graph.search.AStarSearch
-
- calculatePercentInvalid() - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- calculatePercentInvalid() - Method in interface org.encog.ca.universe.Universe
-
- calculatePointsInRange() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Calculate how many points are in the high and low range.
- calculateProbability(BayesianEvent, int, int[]) - Method in class org.encog.ml.bayesian.training.estimator.SimpleEstimator
-
Calculate the probability.
- CalculateRegressionError - Class in org.encog.util.error
-
- CalculateRegressionError() - Constructor for class org.encog.util.error.CalculateRegressionError
-
- calculateRegressionError(MLRegression, MLDataSet) - Static method in class org.encog.util.simple.EncogUtility
-
- calculateRMS() - Method in class org.encog.mathutil.error.ErrorCalculation
-
Calculate the error with RMS.
- CalculateScheduleTimes - Class in org.encog.ml.schedule
-
- CalculateScheduleTimes() - Constructor for class org.encog.ml.schedule.CalculateScheduleTimes
-
- calculateScore() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Subclasses should provide a method that evaluates the score for the
current solution.
- CalculateScore - Interface in org.encog.ml
-
Used by simulated annealing and genetic algorithms to calculate the score
for a machine learning method.
- calculateScore(MLMethod) - Method in interface org.encog.ml.CalculateScore
-
Calculate this network's score.
- calculateScore(MLMethod) - Method in class org.encog.ml.ea.score.EmptyScoreFunction
-
Calculate this network's score.
- calculateScore(Genome) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Calculate the score for a genome.
- calculateScore(Genome) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Calculate the score for a genome.
- calculateScore(MLMethod) - Method in class org.encog.ml.fitness.MultiObjectiveFitness
-
Calculate this network's score.
- calculateScore(MLMethod) - Method in class org.encog.ml.prg.train.ZeroEvalScoreFunction
-
Calculate this network's score.
- calculateScore() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper
-
Used to pass the determineError call on to the parent object.
- calculateScore(MLMethod) - Method in class org.encog.neural.networks.training.TrainingSetScore
-
Calculate the score for the network.
- calculateScoreAdjustment(Genome, List<AdjustScore>) - Static method in class org.encog.ml.ea.train.basic.BasicEA
-
Calculate the score adjustment, based on adjusters.
- calculateShare(boolean, double) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Calculate this genome's share of the next population.
- calculateShare(boolean, double) - Method in interface org.encog.ml.ea.species.Species
-
Calculate this genome's share of the next population.
- calculateSize() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
Calculate the size that an array should be to hold all of the weights and
bias values.
- calculateStartIndex() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Calculate the index to start at.
- calculateUpperStep(DimensionConstraint, int) - Method in class org.encog.mathutil.dimension.MultiDimension
-
- calculateValue(State) - Method in class org.encog.ml.world.learning.mdp.ValueIteration
-
- calculateWorkers() - Method in class org.encog.util.concurrency.DetermineWorkload
-
Calculate the high and low ranges for each worker.
- CalculationCriteria - Interface in org.encog.neural.networks.training.pnn
-
Calculate criteria.
- call() - Method in class org.encog.ml.ea.train.basic.EAWorker
- canContinue() - Method in class org.encog.ml.bayesian.training.TrainBayesian
- canContinue() - Method in class org.encog.ml.ea.train.basic.TrainEA
- canContinue() - Method in class org.encog.ml.fitting.gaussian.TrainGaussian
-
- canContinue() - Method in class org.encog.ml.fitting.linear.TrainLinearRegression
-
- canContinue() - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
- canContinue() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- canContinue() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- canContinue() - Method in class org.encog.ml.svm.training.SVMSearchTrain
- canContinue() - Method in class org.encog.ml.svm.training.SVMTrain
- canContinue() - Method in interface org.encog.ml.train.MLTrain
-
- canContinue() - Method in class org.encog.neural.cpn.training.TrainInstar
- canContinue() - Method in class org.encog.neural.cpn.training.TrainOutstar
- canContinue() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
- canContinue() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
- canContinue() - Method in class org.encog.neural.networks.training.cross.CrossValidationKFold
- canContinue() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
- canContinue() - Method in class org.encog.neural.networks.training.nm.NelderMeadTraining
- canContinue() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
- canContinue() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
- canContinue() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
This training type does not support training continue.
- canContinue() - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
- canContinue() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
- canContinue() - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
This training type does not support training continue.
- canContinue() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
- canContinue() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
- canContinue() - Method in class org.encog.neural.rbf.training.SVDTraining
-
- canContinue() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
- canContinue() - Method in class org.encog.neural.som.training.clustercopy.SOMClusterCopyTraining
- CANT_DEFINE_ACT - Static variable in class org.encog.ml.factory.method.FeedforwardFactory
-
Error.
- CAProgram - Interface in org.encog.ca.program
-
- CARunner - Interface in org.encog.ca.runner
-
- CAVisualizer - Interface in org.encog.ca.visualize
-
- CDATA_BEGIN - Static variable in class org.encog.parse.tags.TagConst
-
The beginning of a CDATA section.
- CDATA_END - Static variable in class org.encog.parse.tags.TagConst
-
THe end of a CDATA section.
- cell(String) - Method in class org.encog.util.HTMLReport
-
- cell(String, int) - Method in class org.encog.util.HTMLReport
-
- CellularAutomataError - Exception in org.encog.ca
-
- CellularAutomataError(String) - Constructor for exception org.encog.ca.CellularAutomataError
-
Construct a message exception.
- CellularAutomataError(Throwable) - Constructor for exception org.encog.ca.CellularAutomataError
-
Construct an exception that holds another exception.
- CellularAutomataError(String, Throwable) - Constructor for exception org.encog.ca.CellularAutomataError
-
Construct an exception that holds another exception.
- Centroid<O> - Interface in org.encog.util.kmeans
-
A centroid.
- centroid() - Method in class org.encog.util.kmeans.Cluster
-
- CentroidFactory<O> - Interface in org.encog.util.kmeans
-
An object that can create centroids.
- CGOLD - Static variable in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
The golden section.
- ChainRuleWorker - Class in org.encog.mathutil.matrices.hessian
-
A threaded worker that is used to calculate the first derivatives of the
output of the neural network.
- ChainRuleWorker(FlatNetwork, MLDataSet, int, int) - Constructor for class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
Construct the chain rule worker.
- changeNeuronCount(int, int) - Method in class org.encog.neural.prune.PruneSelective
-
Change the neuron count for the network.
- CHAR_BULLET - Static variable in class org.encog.parse.tags.read.ReadTags
-
The bullet character.
- CHAR_TRADEMARK - Static variable in class org.encog.parse.tags.read.ReadTags
-
The bullet character.
- characters(char[], int, int) - Method in class org.encog.ml.bayesian.bif.BIFHandler
- checkError() - Method in class org.encog.util.concurrency.EngineConcurrency
-
Check to see if one of the threads has thrown an error.
- CHOICES_TRUE_FALSE - Static variable in class org.encog.ml.bayesian.BayesianNetwork
-
Default choices for a boolean event.
- CholeskyDecomposition - Class in org.encog.mathutil.matrices.decomposition
-
Cholesky Decomposition.
- CholeskyDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition
-
Cholesky algorithm for symmetric and positive definite matrix.
- ChooseObject<T> - Class in org.encog.util.obj
-
This class is used to choose between several objects with a specified probability.
- ChooseObject() - Constructor for class org.encog.util.obj.ChooseObject
-
- chooseRandomNeuron(NEATGenome, boolean) - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
Choose a random neuron.
- chs() - Method in class org.encog.mathutil.ComplexNumber
-
Negative of this complex number (chs stands for change sign).
- clamp(double, double) - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- clamp(double, double) - Method in interface org.encog.ca.universe.ContinuousCell
-
- clampComponents(double[], double) - Method in class org.encog.mathutil.VectorAlgebra
-
For each components, reset their value to maxValue if
their absolute value exceeds it.
- clampWeight(double, double) - Static method in class org.encog.neural.neat.NEATPopulation
-
Change the weight, do not allow the weight to go out of the weight range.
- classify(MLData) - Method in class org.encog.ensemble.GenericEnsembleML
-
- classify(MLData) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Classify the input.
- classify(MLData) - Method in interface org.encog.ml.MLClassification
-
Classify the input into a group.
- classify(MLData) - Method in class org.encog.ml.svm.SVM
-
Classify the input into a group.
- classify(MLData) - Method in class org.encog.neural.art.ART1
-
Classify the input data to a class number.
- classify(MLData) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Classify the input into a group.
- classify(MLData) - Method in class org.encog.neural.networks.BasicNetwork
-
Classify the input into a group.
- classify(MLData) - Method in class org.encog.neural.pnn.BasicPNN
-
Classify the input into a group.
- classify(MLData) - Method in class org.encog.neural.som.SOM
-
Classify the input into a group.
- ClassItem - Class in org.encog.util.arrayutil
-
A class item.
- ClassItem(String, int) - Constructor for class org.encog.util.arrayutil.ClassItem
-
Construct the object.
- clear() - Method in class org.encog.mathutil.matrices.hessian.BasicHessian
-
Clear the Hessian and gradients.
- clear() - Method in interface org.encog.mathutil.matrices.hessian.ComputeHessian
-
Clear the Hessian and gradients.
- clear() - Method in class org.encog.mathutil.matrices.Matrix
-
Set all rows and columns to zero.
- clear() - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Clear any data to zero.
- clear() - Method in class org.encog.ml.data.basic.BasicMLData
-
Clear any data to zero.
- clear() - Method in interface org.encog.ml.data.MLData
-
Clear any data to zero.
- clear() - Method in class org.encog.ml.data.sparse.SparseMLData
-
Clear any data to zero.
- clear() - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Set all data to false.
- clear() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Clear the entire dataset.
- clear() - Method in class org.encog.ml.ea.population.BasicPopulation
-
Clear all genomes from this population.
- clear() - Method in interface org.encog.ml.ea.population.Population
-
Clear all genomes from this population.
- clear() - Method in class org.encog.neural.bam.BAM
-
Clear any connection weights.
- clear() - Method in class org.encog.neural.pattern.ADALINEPattern
-
Clear out any parameters.
- clear() - Method in class org.encog.neural.pattern.ART1Pattern
-
Clear any properties set for this network.
- clear() - Method in class org.encog.neural.pattern.BAMPattern
-
Clear any settings on the pattern.
- clear() - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Clear any properties set on this network.
- clear() - Method in class org.encog.neural.pattern.CPNPattern
-
Clear any parameters that were set.
- clear() - Method in class org.encog.neural.pattern.ElmanPattern
-
Clear out any hidden neurons.
- clear() - Method in class org.encog.neural.pattern.FeedForwardPattern
-
Clear out any hidden neurons.
- clear() - Method in class org.encog.neural.pattern.HopfieldPattern
-
Nothing to clear.
- clear() - Method in class org.encog.neural.pattern.JordanPattern
-
Clear out any hidden neurons.
- clear() - Method in interface org.encog.neural.pattern.NeuralNetworkPattern
-
Clear the hidden layers so that they can be redefined.
- clear() - Method in class org.encog.neural.pattern.PNNPattern
-
Clear out any hidden neurons.
- clear() - Method in class org.encog.neural.pattern.RadialBasisPattern
-
Clear out any hidden neurons.
- clear() - Method in class org.encog.neural.pattern.SOMPattern
-
Clear out any hidden neurons.
- clear() - Method in class org.encog.neural.pattern.SVMPattern
-
Clear any settings on the pattern.
- clear() - Method in class org.encog.neural.thermal.ThermalNetwork
-
Clear any connection weights.
- clear() - Method in class org.encog.parse.tags.Tag
-
Clear the name, type and attributes.
- clear() - Method in class org.encog.util.arrayutil.WindowDouble
-
Clear the contents of the window.
- clear() - Method in class org.encog.util.HTMLReport
-
- clear() - Method in class org.encog.util.obj.ChooseObject
-
CLear all objects from the collection.
- clear() - Method in class org.encog.util.text.BagOfWords
-
- clearConnectionLimit() - Method in class org.encog.neural.flat.FlatNetwork
-
Clear any connection limits.
- clearContext() - Method in interface org.encog.ml.MLContext
-
Clear the context.
- clearContext() - Method in class org.encog.neural.flat.FlatNetwork
-
Clear any context neurons.
- clearContext() - Method in class org.encog.neural.freeform.FreeformNetwork
-
Clear the context.
- clearContext() - Method in class org.encog.neural.networks.BasicNetwork
-
Clear any data from any context layers.
- clearDefinedVariables() - Method in class org.encog.ml.prg.EncogProgramContext
-
Clear the defined variables.
- clearFilenames() - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Clear out all filenames.
- clearInputOutput() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Clear the input/output columns, but not the source columns.
- clearPerformers() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Clear all of the performers.
- clearQueue() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Clear the workload.
- clearTasks() - Method in class org.encog.app.analyst.script.AnalystScript
-
Clear all tasks.
- clearTempTraining() - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Clear the temp training.
- clearTempTraining() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Clear the temp training.
- clearTempTraining() - Method in interface org.encog.neural.freeform.TempTrainingData
-
Clear the temp training.
- clone() - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- clone() - Method in interface org.encog.ca.universe.Universe
-
- clone() - Method in class org.encog.engine.network.activation.ActivationBiPolar
-
- clone() - Method in class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
- clone() - Method in class org.encog.engine.network.activation.ActivationClippedLinear
- clone() - Method in class org.encog.engine.network.activation.ActivationCompetitive
-
- clone() - Method in class org.encog.engine.network.activation.ActivationElliott
-
- clone() - Method in class org.encog.engine.network.activation.ActivationElliottSymmetric
-
- clone() - Method in interface org.encog.engine.network.activation.ActivationFunction
-
- clone() - Method in class org.encog.engine.network.activation.ActivationGaussian
-
- clone() - Method in class org.encog.engine.network.activation.ActivationLinear
-
- clone() - Method in class org.encog.engine.network.activation.ActivationLOG
-
- clone() - Method in class org.encog.engine.network.activation.ActivationRamp
-
Clone the object.
- clone() - Method in class org.encog.engine.network.activation.ActivationSigmoid
-
- clone() - Method in class org.encog.engine.network.activation.ActivationSIN
-
- clone() - Method in class org.encog.engine.network.activation.ActivationSoftMax
-
- clone() - Method in class org.encog.engine.network.activation.ActivationSteepenedSigmoid
-
- clone() - Method in class org.encog.engine.network.activation.ActivationStep
-
- clone() - Method in class org.encog.engine.network.activation.ActivationTANH
-
- clone() - Method in class org.encog.mathutil.IntPair
-
- clone() - Method in class org.encog.mathutil.libsvm.svm_parameter
-
- clone() - Method in class org.encog.mathutil.matrices.Matrix
-
Create a copy of the matrix.
- clone() - Method in class org.encog.ml.bayesian.query.BasicQuery
-
- clone() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- clone() - Method in class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
-
- clone() - Method in class org.encog.ml.bayesian.query.sample.SamplingQuery
-
- clone() - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Clone this object.
- clone() - Method in class org.encog.ml.data.basic.BasicMLData
-
Clone this object.
- clone() - Method in class org.encog.ml.data.basic.BasicMLDataSet
- clone() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
- clone() - Method in interface org.encog.ml.data.MLData
-
Clone this object.
- clone() - Method in class org.encog.ml.data.sparse.SparseMLData
-
Clone this object.
- clone() - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
- clone() - Method in class org.encog.ml.hmm.distributions.ContinousDistribution
- clone() - Method in class org.encog.ml.hmm.distributions.DiscreteDistribution
-
- clone() - Method in interface org.encog.ml.hmm.distributions.StateDistribution
-
- clone() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- clone() - Method in class org.encog.neural.flat.FlatNetwork
-
Clone the network.
- clone() - Method in class org.encog.neural.flat.FlatNetworkRBF
-
Clone the network.
- clone() - Method in class org.encog.neural.freeform.FreeformNetwork
-
Return a clone of this neural network.
- clone() - Method in class org.encog.neural.networks.BasicNetwork
-
Return a clone of this neural network.
- clone() - Method in class org.encog.parse.tags.Tag
-
- cloneBranch(EncogProgram, ProgramNode) - Method in class org.encog.ml.prg.EncogProgramContext
-
Clone a branch of the program from the specified node.
- cloneFlatNetwork(FlatNetwork) - Method in class org.encog.neural.flat.FlatNetwork
-
Clone into the flat network passed in.
- cloneProgram(EncogProgram) - Method in class org.encog.ml.prg.EncogProgramContext
-
Clone an entire program, keep the same context.
- cloneStructure() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- CLOSE - Static variable in class org.encog.app.analyst.csv.basic.FileData
-
The close value.
- close() - Method in class org.encog.app.quant.ninja.NinjaStreamWriter
-
Close the file.
- close() - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- close() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- close() - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
Close this datasource and release any resources obtained by it, including
any iterators created.
- close() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
Close this datasource and release any resources obtained by it, including
any iterators created.
- close() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Close the dataset.
- close() - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
Close any open files.
- close() - Method in class org.encog.ml.data.buffer.codec.CSVDataCODEC
-
Close any open files.
- close() - Method in interface org.encog.ml.data.buffer.codec.DataSetCODEC
-
Close any open files.
- close() - Method in class org.encog.ml.data.buffer.codec.ExcelCODEC
-
Close any open files.
- close() - Method in class org.encog.ml.data.buffer.codec.NeuralDataSetCODEC
-
Close any open files.
- close() - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
-
Close any open files.
- close() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Close the file.
- close() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Close the dataset.
- close() - Method in interface org.encog.ml.data.MLDataSet
-
Close this datasource and release any resources obtained by it, including
any iterators created.
- close() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
Close this datasource and release any resources obtained by it, including
any iterators created.
- close() - Method in class org.encog.parse.tags.write.WriteTags
-
Close this object.
- close() - Method in class org.encog.persist.EncogReadHelper
-
Close the file.
- close() - Method in class org.encog.util.csv.ReadCSV
-
Close the file.
- close() - Method in interface org.encog.util.normalize.target.NormalizationStorage
-
Open the storage.
- close() - Method in class org.encog.util.normalize.target.NormalizationStorageArray1D
-
Not needed for this storage type.
- close() - Method in class org.encog.util.normalize.target.NormalizationStorageArray2D
-
Not needed for this storage type.
- close() - Method in class org.encog.util.normalize.target.NormalizationStorageCSV
-
Close the CSV file.
- close() - Method in class org.encog.util.normalize.target.NormalizationStorageEncogCollection
-
- close() - Method in class org.encog.util.normalize.target.NormalizationStorageNeuralDataSet
-
Not needed for this storage type.
- close() - Method in class org.encog.util.text.Base64.OutputStream
-
Flushes and closes (I think, in the superclass) the stream.
- cluster(int) - Method in class org.encog.ml.hmm.train.kmeans.Clusters
-
- cluster(MLDataPair) - Method in class org.encog.ml.hmm.train.kmeans.Clusters
-
- Cluster<T extends CentroidFactory<? super T>> - Class in org.encog.util.kmeans
-
A cluster.
- Cluster() - Constructor for class org.encog.util.kmeans.Cluster
-
Create an empty cluster.
- Cluster(T) - Constructor for class org.encog.util.kmeans.Cluster
-
Create a cluster with one initial data point.
- CLUSTER_CONFIG_CLUSTERS - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "CLUSTER:CONFIG_clusters".
- CLUSTER_CONFIG_SOURCE_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "CLUSTER:CONFIG_sourceFile".
- CLUSTER_CONFIG_TARGET_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "CLUSTER:CONFIG_targetFile".
- CLUSTER_CONFIG_TYPE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "CLUSTER:CONFIG_type".
- Clusters - Class in org.encog.ml.hmm.train.kmeans
-
Clusters used for the KMeans HMM training algorithm.
- Clusters(int, MLDataSet) - Constructor for class org.encog.ml.hmm.train.kmeans.Clusters
-
- ClusterSOMFactory - Class in org.encog.ml.factory.train
-
Create a trainer that uses the SOM cluster training method.
- ClusterSOMFactory() - Constructor for class org.encog.ml.factory.train.ClusterSOMFactory
-
- Cmd - Class in org.encog.app.analyst.commands
-
Base class for Encog Analyst commands.
- Cmd(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.Cmd
-
Construct this command.
- CmdBalance - Class in org.encog.app.analyst.commands
-
Performs the balance command.
- CmdBalance(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdBalance
-
Construct the balance command.
- CmdCluster - Class in org.encog.app.analyst.commands
-
This command is used to randomize the lines in a CSV file.
- CmdCluster(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdCluster
-
Construct the cluster command.
- CmdCode - Class in org.encog.app.analyst.commands
-
This command is used to generate the binary EGB file from a CSV file.
- CmdCode(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdCode
-
Construct this generate command.
- CmdCreate - Class in org.encog.app.analyst.commands
-
The Encog Analyst create command.
- CmdCreate(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdCreate
-
Construct the create command.
- CmdEvaluate - Class in org.encog.app.analyst.commands
-
This class is used to evaluate a machine learning method.
- CmdEvaluate(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdEvaluate
-
Construct the evaluate command.
- CmdEvaluateRaw - Class in org.encog.app.analyst.commands
-
This class is used to evaluate a machine learning method.
- CmdEvaluateRaw(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdEvaluateRaw
-
Construct an evaluate raw command.
- CmdGenerate - Class in org.encog.app.analyst.commands
-
This command is used to generate the binary EGB file from a CSV file.
- CmdGenerate(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdGenerate
-
Construct this generate command.
- CmdNormalize - Class in org.encog.app.analyst.commands
-
The normalize command is used to normalize data.
- CmdNormalize(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdNormalize
-
Construct the normalize command.
- CmdProcess - Class in org.encog.app.analyst.commands
-
This command is used to preprocess a CSV file.
- CmdProcess(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdProcess
-
Construct the randomize command.
- CmdRandomize - Class in org.encog.app.analyst.commands
-
This command is used to randomize the lines in a CSV file.
- CmdRandomize(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdRandomize
-
Construct the randomize command.
- CmdReset - Class in org.encog.app.analyst.commands
-
Analyst command that allows all properties to be reset to what they were
originally loaded from the Encog EGA file.
- CmdReset(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdReset
-
Construct the reset command.
- CmdSegregate - Class in org.encog.app.analyst.commands
-
This command is used to segregate one CSV file into several.
- CmdSegregate(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdSegregate
-
Construct the segregate command.
- CmdSet - Class in org.encog.app.analyst.commands
-
The set command allows a script to override a property value.
- CmdSet(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdSet
-
Construct the set command with the analyst.
- CmdTrain - Class in org.encog.app.analyst.commands
-
This command is used to perform training on a machine learning method and
dataset.
- CmdTrain(EncogAnalyst) - Constructor for class org.encog.app.analyst.commands.CmdTrain
-
Construct the train command.
- code(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames
-
Get the code for a TimeUnit.
- code(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames
-
Get the code for the specified time unit.
- CODE_CONFIG_EMBED_DATA - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "GENERATE:CONFIG_embedData".
- CODE_CONFIG_TARGET_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "GENERATE:CONFIG_targetFile".
- CODE_CONFIG_TARGET_LANGUAGE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "GENERATE:CONFIG_targetLanguage".
- CodeDataUnit - Class in org.encog.bot.dataunit
-
A data unit that holds code.
- CodeDataUnit() - Constructor for class org.encog.bot.dataunit.CodeDataUnit
-
- coef0 - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- COLS - Static variable in class org.encog.persist.PersistConst
-
- COLUMN_FIVE - Static variable in class org.encog.app.analyst.script.ScriptLoad
-
Column 5.
- COLUMN_FOUR - Static variable in class org.encog.app.analyst.script.ScriptLoad
-
Column 4.
- COLUMN_ONE - Static variable in class org.encog.app.analyst.script.ScriptLoad
-
Column 1.
- COLUMN_THREE - Static variable in class org.encog.app.analyst.script.ScriptLoad
-
Column 3.
- COLUMN_TWO - Static variable in class org.encog.app.analyst.script.ScriptLoad
-
Column 2.
- ColumnDefinition - Class in org.encog.ml.data.versatile.columns
-
Defines a column definition.
- ColumnDefinition(String, ColumnType) - Constructor for class org.encog.ml.data.versatile.columns.ColumnDefinition
-
The column definition.
- columnIndex(String) - Method in class org.encog.ml.data.versatile.sources.CSVDataSource
-
Obtain the column index for the specified name.
- columnIndex(String) - Method in interface org.encog.ml.data.versatile.sources.VersatileDataSource
-
Obtain the column index for the specified name.
- ColumnType - Enum in org.encog.ml.data.versatile.columns
-
The type of column, defined using level of measurement.
- combine(long, int) - Static method in class org.encog.util.time.NumericDateUtil
-
- COMMA - Static variable in class org.encog.persist.EncogWriteHelper
-
A comma char.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdBalance
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdCluster
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdCode
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdCreate
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdEvaluate
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdEvaluateRaw
-
The name of the command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdGenerate
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdNormalize
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdProcess
-
The name of the command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdRandomize
-
The name of the command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdReset
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdSegregate
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdSet
-
The name of this command.
- COMMAND_NAME - Static variable in class org.encog.app.analyst.commands.CmdTrain
-
The name of this command.
- COMMENT_BEGIN - Static variable in class org.encog.parse.tags.TagConst
-
The beginning of a comment.
- COMMENT_END - Static variable in class org.encog.parse.tags.TagConst
-
The end of a comment.
- CommonRender - Class in org.encog.parse.expression
-
Common functions for some renders.
- CommonRender() - Constructor for class org.encog.parse.expression.CommonRender
-
- compare(LoadedRow, LoadedRow) - Method in class org.encog.app.analyst.csv.sort.RowComparator
-
Compare two LoadedRow objects.
- compare(Universe) - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- compare(Universe) - Method in interface org.encog.ca.universe.Universe
-
- compare(Genome, Genome) - Method in class org.encog.ml.ea.sort.MaximizeAdjustedScoreComp
- compare(Genome, Genome) - Method in class org.encog.ml.ea.sort.MaximizeScoreComp
- compare(Genome, Genome) - Method in class org.encog.ml.ea.sort.MinimizeAdjustedScoreComp
- compare(Genome, Genome) - Method in class org.encog.ml.ea.sort.MinimizeScoreComp
- compare(Genome, Genome) - Method in class org.encog.ml.ea.sort.SortGenomesForSpecies
- compare(Species, Species) - Method in class org.encog.ml.ea.sort.SpeciesComparator
- compare(EncogProgram, EncogProgram) - Method in class org.encog.ml.prg.species.CompareEncogProgram
-
Compare program 1 and 2 node for node.
- compareArgs(int[]) - Method in class org.encog.ml.bayesian.table.TableLine
-
Compare this truth line's arguments to others.
- CompareEncogProgram - Class in org.encog.ml.prg.species
-
Compare two Encog programs for speciation.
- CompareEncogProgram() - Constructor for class org.encog.ml.prg.species.CompareEncogProgram
-
- compareTo(AnalystClassItem) - Method in class org.encog.app.analyst.script.AnalystClassItem
- compareTo(PropertyEntry) - Method in class org.encog.app.analyst.script.prop.PropertyEntry
- compareTo(Trans) - Method in class org.encog.ca.program.generic.Trans
-
- compareTo(BayesianChoice) - Method in class org.encog.ml.bayesian.BayesianChoice
- compareTo(LoadedMarketData) - Method in class org.encog.ml.data.market.loader.LoadedMarketData
- compareTo(TemporalPoint) - Method in class org.encog.ml.data.temporal.TemporalPoint
- compareTo(SuccessorState) - Method in class org.encog.ml.world.SuccessorState
-
- compareTo(NEATLink) - Method in class org.encog.neural.neat.NEATLink
- compareTo(NEATBaseGene) - Method in class org.encog.neural.neat.training.NEATBaseGene
- compatibleTypes(List<ValueType>, List<ValueType>) - Static method in class org.encog.ml.prg.opp.LevelHolder
-
Determine if the specified child types are compatible with the parent types.
- compileEPL(String) - Method in class org.encog.ml.prg.EncogProgram
-
Compile the specified EPL into an actual program node structure, for
later execution.
- compileExpression(String) - Method in class org.encog.ml.prg.EncogProgram
-
Compile the specified expression.
- complete() - Method in class org.encog.util.http.FormUtility
-
Complete the building of the form.
- completePass1() - Method in class org.encog.app.analyst.analyze.AnalyzedField
-
Complete pass 1.
- completePass2() - Method in class org.encog.app.analyst.analyze.AnalyzedField
-
Complete pass 2.
- ComplexityAdjustedScore - Class in org.encog.ml.ea.score.adjust
-
Adjust scores to penalize complexity.
- ComplexityAdjustedScore(int, int, double, double) - Constructor for class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
Construct a adjustor to penalize complexity.
- ComplexityAdjustedScore() - Constructor for class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- ComplexNumber - Class in org.encog.mathutil
-
A complex number class.
- ComplexNumber(double, double) - Constructor for class org.encog.mathutil.ComplexNumber
-
Constructs the complex number z = u + i*v
- ComplexNumber(ComplexNumber) - Constructor for class org.encog.mathutil.ComplexNumber
-
Create a complex number from another complex number.
- CompoundOperator - Class in org.encog.ml.ea.opp
-
A compound operator randomly chooses sub-operators to perform the actual
operation.
- CompoundOperator() - Constructor for class org.encog.ml.ea.opp.CompoundOperator
-
- compute(MLData) - Method in class org.encog.ensemble.Ensemble
-
Compute the output for a specific input
- compute(MLData) - Method in class org.encog.ensemble.GenericEnsembleML
-
- compute() - Method in interface org.encog.mathutil.matrices.hessian.ComputeHessian
-
Compute the Hessian.
- compute() - Method in class org.encog.mathutil.matrices.hessian.HessianCR
-
Compute the Hessian.
- compute() - Method in class org.encog.mathutil.matrices.hessian.HessianFD
-
Compute the Hessian.
- compute(MLData) - Method in class org.encog.ml.fitting.gaussian.GaussianFitting
-
- compute(MLData) - Method in class org.encog.ml.fitting.linear.LinearRegression
-
- compute(MLData) - Method in interface org.encog.ml.MLRegression
-
Compute regression.
- compute(MLData) - Method in class org.encog.ml.prg.EncogProgram
-
Compute the output from the input MLData.
- compute(MLData) - Method in class org.encog.ml.prg.train.PrgPopulation
-
Compute the output from the best Genome.
- compute(MLData) - Method in class org.encog.ml.svm.SVM
-
Compute the output for the given input.
- compute(BiPolarNeuralData, BiPolarNeuralData) - Method in class org.encog.neural.art.ART1
-
Compute the output from the ART1 network.
- compute(MLData) - Method in class org.encog.neural.art.ART1
-
Compute the output for the BasicNetwork class.
- compute(MLData) - Method in class org.encog.neural.bam.BAM
-
Setup the network logic, read parameters from the network.
- compute(NeuralDataMapping) - Method in class org.encog.neural.bam.BAM
-
Compute the network for the specified input.
- compute(MLData) - Method in class org.encog.neural.cpn.CPN
-
Compute regression.
- compute(double[], double[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Calculate the output for the given input.
- compute(double[], double[]) - Method in class org.encog.neural.flat.FlatNetworkRBF
-
Calculate the output for the given input.
- compute(MLData) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Compute regression.
- compute(MLData) - Method in class org.encog.neural.neat.NEATNetwork
-
Compute the output from this synapse.
- compute(MLData) - Method in class org.encog.neural.neat.NEATPopulation
-
Compute regression.
- compute(double[], double[]) - Method in class org.encog.neural.networks.BasicNetwork
-
Compute the output for this network.
- compute(MLData) - Method in class org.encog.neural.networks.BasicNetwork
-
Compute the output for a given input to the neural network.
- compute(MLData) - Method in class org.encog.neural.pnn.AbstractPNN
-
Compute the output from the network.
- compute(MLData) - Method in class org.encog.neural.pnn.BasicPNN
-
Compute the output from this network.
- compute(MLData) - Method in class org.encog.neural.rbf.RBFNetwork
-
Compute regression.
- compute(MLData) - Method in class org.encog.neural.thermal.BoltzmannMachine
-
Note: for Boltzmann networks, you will usually want to call the "run"
method to compute the output.
- compute(MLData) - Method in class org.encog.neural.thermal.HopfieldNetwork
-
Note: for Hopfield networks, you will usually want to call the "run"
method to compute the output.
- computeAlpha(HiddenMarkovModel, MLDataSet) - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Compute alpha.
- computeAlpha(HiddenMarkovModel, MLDataSet) - Method in class org.encog.ml.hmm.alog.ForwardBackwardScaledCalculator
-
- computeAlphaInit(HiddenMarkovModel, MLDataPair, int) - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Compute the alpha init.
- computeAlphaStep(HiddenMarkovModel, MLDataPair, int, int) - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Compute the alpha step.
- computeBeta(HiddenMarkovModel, MLDataSet) - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Compute the beta step.
- computeBeta(HiddenMarkovModel, MLDataSet) - Method in class org.encog.ml.hmm.alog.ForwardBackwardScaledCalculator
-
- computeBetaStep(HiddenMarkovModel, MLDataPair, int, int) - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Compute the beta step.
- computeDeriv(MLData, MLData) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Compute the derivative for target data.
- computeDistance(String, String) - Static method in class org.encog.util.text.LevenshteinDistance
-
- ComputeHessian - Interface in org.encog.mathutil.matrices.hessian
-
Compute (estimate) the Hessian matrix.
- computeInstar(MLData) - Method in class org.encog.neural.cpn.CPN
-
Compute the instar layer.
- computeLayer(int) - Method in class org.encog.neural.flat.FlatNetwork
-
Calculate a layer.
- computeOutstar(MLData) - Method in class org.encog.neural.cpn.CPN
-
Compute the outstar layer.
- computeProbability(MLData) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- ConcurrentJob - Class in org.encog.util.concurrency.job
-
This class forms the basis for a job that can be run concurrently.
- ConcurrentJob(StatusReportable) - Constructor for class org.encog.util.concurrency.job.ConcurrentJob
-
Construct a concurrent job.
- ConcurrentTrainingManager - Class in org.encog.neural.networks.training.concurrent
-
Concurrent training manager.
- ConcurrentTrainingPerformer - Interface in org.encog.neural.networks.training.concurrent.performers
-
Performers actually perform the training.
- ConcurrentTrainingPerformerCPU - Class in org.encog.neural.networks.training.concurrent.performers
-
This performer allows jobs to be performed by the CPU.
- ConcurrentTrainingPerformerCPU(int) - Constructor for class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
-
Construct the performer.
- cond() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Two norm condition number
- conj() - Method in class org.encog.mathutil.ComplexNumber
-
Complex conjugate of this Complex number
(the conjugate of x+i*y is x-i*y).
- connect(BasicNode, BasicNode, double) - Method in class org.encog.ml.graph.BasicGraph
-
- connect(BasicNode, double) - Method in class org.encog.ml.graph.BasicNode
-
- ConnectionTask - Interface in org.encog.neural.freeform.task
-
Implements a task that will be performed for every connection.
- connectLayers(FreeformLayer, FreeformLayer) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Connect two layers.
- connectLayers(FreeformLayer, FreeformLayer, ActivationFunction, double, boolean) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Connect two layers.
- ConnectLayers(FreeformLayer, FreeformLayer, ActivationFunction) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Connect two layers, assume bias activation of 1.0 and non-recurrent
connection.
- ConsistentRandomizer - Class in org.encog.mathutil.randomize
-
A randomizer that takes a seed and will always produce consistent results.
- ConsistentRandomizer(double, double) - Constructor for class org.encog.mathutil.randomize.ConsistentRandomizer
-
Construct a range randomizer.
- ConsistentRandomizer(double, double, int) - Constructor for class org.encog.mathutil.randomize.ConsistentRandomizer
-
Construct a range randomizer.
- ConsoleAnalystListener - Class in org.encog.app.analyst
-
A console implementation of the Encog Analyst listener.
- ConsoleAnalystListener() - Constructor for class org.encog.app.analyst.ConsoleAnalystListener
-
- ConsoleStatusReportable - Class in org.encog
-
A simple status report that goes to the console.
- ConsoleStatusReportable() - Constructor for class org.encog.ConsoleStatusReportable
-
- ConstMutation - Class in org.encog.ml.prg.opp
-
Mutate the constant nodes of an Encog program.
- ConstMutation(EncogProgramContext, double, double) - Constructor for class org.encog.ml.prg.opp.ConstMutation
-
Construct a const mutator.
- ConstraintRule - Interface in org.encog.ml.ea.rules
-
Defines a constraint.
- ConstRandomizer - Class in org.encog.mathutil.randomize
-
A randomizer that will create always set the random number to a const value,
used mainly for testing.
- ConstRandomizer(double) - Constructor for class org.encog.mathutil.randomize.ConstRandomizer
-
Construct a range randomizer.
- constructNEATTrainer(CalculateScore, int, int, int) - Static method in class org.encog.neural.neat.NEATUtil
-
- constructNEATTrainer(NEATPopulation, CalculateScore) - Static method in class org.encog.neural.neat.NEATUtil
-
Construct a NEAT (or HyperNEAT trainer.
- constructURL(URL, String, boolean) - Static method in class org.encog.util.http.URLUtility
-
Construct a URL from its basic parts.
- contains(int[], int) - Static method in class org.encog.util.EngineArray
-
- contains(String) - Method in class org.encog.util.text.BagOfWords
-
- containsDestination(BasicNode) - Method in class org.encog.ml.graph.search.FrontierHolder
-
- ContainsFlat - Interface in org.encog.neural.networks
-
Interface that specifies that a machine learning method contains a
flat network.
- containsInvalidURLCharacters(String) - Static method in class org.encog.util.http.URLUtility
-
Returns true if the URL contains any invalid characters.
- contents() - Method in class org.encog.mathutil.probability.vars.VariableList
-
- ContinousDistribution - Class in org.encog.ml.hmm.distributions
-
A continuous distribution represents an infinite range of choices between two
real numbers.
- ContinousDistribution(double[], double[][]) - Constructor for class org.encog.ml.hmm.distributions.ContinousDistribution
-
Construct a continuous distribution.
- ContinousDistribution(int) - Constructor for class org.encog.ml.hmm.distributions.ContinousDistribution
-
Construct a continuous distribution with the specified number of dimensions.
- ContinuousCell - Interface in org.encog.ca.universe
-
- Convert - Class in org.encog.mathutil
-
This class is used to convert strings into numeric values.
- convertBack(double) - Method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
Convert a number back after its been normalized.
- convertCSV2Binary(File, File, int, int, boolean) - Static method in class org.encog.util.simple.EncogUtility
-
Convert a CSV file to a binary training file.
- convertCSV2Binary(String, String, int, int, boolean) - Static method in class org.encog.util.simple.EncogUtility
-
Convert a CSV file to a binary training file.
- convertCSV2Binary(File, CSVFormat, File, int[], int[], boolean) - Static method in class org.encog.util.simple.EncogUtility
-
- convertDoubleToString(double[], int) - Static method in class org.encog.util.text.DoubleString
-
- convertFilename(String, URL, boolean) - Static method in class org.encog.util.http.URLUtility
-
Convert a filename for local storage.
- ConvertStringConst - Class in org.encog.app.analyst.util
-
Convert several Analyst String to the correct object.
- convertStringToDouble(String, double[], int) - Static method in class org.encog.util.text.DoubleString
-
- convertToCSVFormat(AnalystFileFormat) - Static method in class org.encog.app.analyst.util.ConvertStringConst
-
Convert an analyst format to a csv format.
- ConwayProgram - Class in org.encog.ca.program.conway
-
- ConwayProgram(Universe) - Constructor for class org.encog.ca.program.conway.ConwayProgram
-
- CookieUtility - Class in org.encog.util.http
-
This class allows URLConnection objects to process cookies.
- CookieUtility() - Constructor for class org.encog.util.http.CookieUtility
-
- copy(UniverseCell) - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- copy(UniverseCell) - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- copy(Universe) - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- copy(Universe) - Method in interface org.encog.ca.universe.Universe
-
- copy(UniverseCell) - Method in interface org.encog.ca.universe.UniverseCell
-
- copy(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Copy from one matrix to another.
- copy(double[], double[]) - Method in class org.encog.mathutil.VectorAlgebra
-
dst = src
Copy a vector.
- copy(Genome) - Method in interface org.encog.ml.ea.genome.Genome
-
Copy from the specified genome into this one.
- copy(ArrayGenome, int, int) - Method in interface org.encog.ml.genetic.genome.ArrayGenome
-
Copy elements from another array genome into this one.
- copy(ArrayGenome, int, int) - Method in class org.encog.ml.genetic.genome.DoubleArrayGenome
-
Copy elements from another array genome into this one.
- copy(Genome) - Method in class org.encog.ml.genetic.genome.DoubleArrayGenome
-
Copy from the specified genome into this one.
- copy(ArrayGenome, int, int) - Method in class org.encog.ml.genetic.genome.IntegerArrayGenome
-
Copy elements from another array genome into this one.
- copy(Genome) - Method in class org.encog.ml.genetic.genome.IntegerArrayGenome
-
Copy from the specified genome into this one.
- copy(Genome) - Method in class org.encog.ml.prg.EncogProgram
-
Copy from the specified genome into this one.
- copy(Genome) - Method in class org.encog.neural.neat.training.NEATGenome
-
Copy from the specified genome into this one.
- copy(NEATLinkGene) - Method in class org.encog.neural.neat.training.NEATLinkGene
-
Copy from another gene.
- copy(NEATNeuronGene) - Method in class org.encog.neural.neat.training.NEATNeuronGene
-
Copy another gene to this one.
- copy(NeuralDataMapping, NeuralDataMapping) - Static method in class org.encog.neural.networks.NeuralDataMapping
-
Copy from one object to the other.
- copy(File, File) - Static method in class org.encog.util.file.FileUtil
-
- copy(InputStream, OutputStream) - Static method in class org.encog.util.file.FileUtil
-
- copyFile(File, File) - Static method in class org.encog.util.file.Directory
-
Copy the specified file.
- copyFromNetwork(FlatNetwork) - Method in class org.encog.neural.networks.training.cross.NetworkFold
-
Copy the weights and output from the network.
- copyResource(String, File) - Static method in class org.encog.util.file.FileUtil
-
- COPYRIGHT - Static variable in class org.encog.Encog
-
The current engog version, this should be read from the properties.
- copyToNetwork(FlatNetwork) - Method in class org.encog.neural.networks.training.cross.NetworkFold
-
Copy weights and output to the network.
- copyWindow(double[], int) - Method in class org.encog.util.arrayutil.VectorWindow
-
Copy the entire window to a complete vector.
- cos(double) - Static method in class org.encog.mathutil.BoundMath
-
Calculate the cos.
- cos() - Method in class org.encog.mathutil.ComplexNumber
-
Cosine of this Complex number (doesn't change this Complex number).
- cosh() - Method in class org.encog.mathutil.ComplexNumber
-
Hyperbolic cosine of this Complex number
(doesn't change this Complex number).
- CostEstimator - Interface in org.encog.ml.graph.search
-
- countActiveFields() - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
-
- countInputFields() - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
Count the number of input fields, or fields used to predict.
- countPredictFields() - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
Count the number of fields that are that are in the prediction.
- CPN - Class in org.encog.neural.cpn
-
Counterpropagation Neural Networks (CPN) were developed by Professor
Robert Hecht-Nielsen in 1987.
- CPN(int, int, int, int) - Constructor for class org.encog.neural.cpn.CPN
-
Construct the counterpropagation neural network.
- CPNPattern - Class in org.encog.neural.pattern
-
Pattern that creates a CPN neural network.
- CPNPattern() - Constructor for class org.encog.neural.pattern.CPNPattern
-
- create(int, int) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Create a new RGB file.
- create(String, int, int) - Method in class org.encog.ml.factory.method.BayesianFactory
-
Create a bayesian network.
- create(String, int, int) - Method in class org.encog.ml.factory.method.EPLFactory
-
Create a feed forward network.
- create(String, int, int) - Method in class org.encog.ml.factory.method.FeedforwardFactory
-
Create a feed forward network.
- create(String, int, int) - Method in class org.encog.ml.factory.method.NEATFactory
-
Create a NEAT population.
- create(String, int, int) - Method in class org.encog.ml.factory.method.PNNFactory
-
Create a PNN network.
- create(String, int, int) - Method in class org.encog.ml.factory.method.RBFNetworkFactory
-
Create a RBF network.
- create(String, int, int) - Method in class org.encog.ml.factory.method.SOMFactory
-
Create a SOM.
- create(String, int, int) - Method in class org.encog.ml.factory.method.SRNFactory
-
Create the SRN.
- create(String, int, int) - Method in class org.encog.ml.factory.method.SVMFactory
-
Create the SVM.
- create(String) - Method in class org.encog.ml.factory.MLActivationFactory
-
- create(String, String, int, int) - Method in class org.encog.ml.factory.MLMethodFactory
-
Create a new machine learning method.
- create(MLMethod, MLDataSet, String, String) - Method in class org.encog.ml.factory.MLTrainFactory
-
Create a trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.AnnealFactory
-
Create an annealing trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.BackPropFactory
-
Create a backpropagation trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.ClusterSOMFactory
-
Create a cluster SOM trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.EPLGAFactory
-
Create an EPL GA trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.GeneticFactory
-
Create an annealing trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.LMAFactory
-
Create a LMA trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.ManhattanFactory
-
Create a Manhattan trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.NEATGAFactory
-
Create an NEAT GA trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.NeighborhoodSOMFactory
-
Create a LMA trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.NelderMeadFactory
-
Create a Nelder Mead trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.PNNTrainFactory
-
Create a PNN trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.PSOFactory
-
Create a PSO trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.QuickPropFactory
-
Create a quick propagation trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.RBFSVDFactory
-
Create a RBF-SVD trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.RPROPFactory
-
Create a RPROP trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.SCGFactory
-
Create a SCG trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.SVMFactory
-
Create a SVM trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.SVMSearchFactory
-
Create a SVM trainer.
- create(MLMethod, MLDataSet, String) - Method in class org.encog.ml.factory.train.TrainBayesianFactory
-
Create a K2 trainer.
- createAbsorbingState(State, double) - Method in class org.encog.ml.world.basic.BasicWorld
-
- createActivationFunction(String) - Method in interface org.encog.plugin.EncogPluginService1
-
Create an activation function.
- createActivationFunction(String) - Method in class org.encog.plugin.system.SystemActivationPlugin
-
Create an activation function.
- createActivationFunction(String) - Method in class org.encog.plugin.system.SystemMethodsPlugin
-
Create an activation function.
- createActivationFunction(String) - Method in class org.encog.plugin.system.SystemTrainingPlugin
-
This plugin does not support activation functions, so it will
always return null.
- createActivations(FlatNetwork) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Create an array of activations based on a flat network.
- createAll(EncogProgramContext) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add all known opcodes to a context.
- createArray(String, double[]) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Create an array.
- createBasicFunctions(EncogProgramContext) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add the opcodes for basic operations to a context.
- createBooleanOperators(EncogProgramContext) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add the opcodes for boolean operations to a context.
- createCentroid() - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Not supported.
- createCentroid() - Method in class org.encog.ml.data.basic.BasicMLData
- createCentroid() - Method in class org.encog.ml.data.basic.BasicMLDataPair
- createCentroid() - Method in class org.encog.ml.data.sparse.SparseMLData
-
- createCentroid() - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Not supported.
- createCentroid() - Method in interface org.encog.util.kmeans.CentroidFactory
-
- createClass(String) - Method in class org.encog.app.generate.program.EncogGenProgram
-
Create a new class.
- createCoefficients() - Method in class org.encog.mathutil.matrices.hessian.HessianFD
-
Compute finite difference coefficients according to the method provided here:
http://en.wikipedia.org/wiki/Finite_difference_coefficients
- createColumnMatrix(double[]) - Static method in class org.encog.mathutil.matrices.Matrix
-
Turn an array of doubles into a column matrix.
- createContext(FreeformLayer, FreeformLayer) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Create a context connection, such as those used by Jordan/Elmann.
- createConversionFunctions(EncogProgramContext) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add the opcodes for type conversion operations to a context.
- createDataSet() - Method in class org.encog.ml.kmeans.BasicCluster
-
Create a dataset from the clustered data.
- createDataSet() - Method in interface org.encog.ml.MLCluster
-
Create a machine learning dataset from the data.
- createDate(int, int, int) - Static method in class org.encog.util.time.DateUtil
-
Create a Date object with the specified date.
- createDependency(BayesianEvent, BayesianEvent) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Create a dependency between two events.
- createDependency(BayesianEvent, BayesianEvent...) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Create a dependency between a parent and multiple children.
- createDependency(String, String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Create a dependency between two labels.
- createElman(int, int, int, ActivationFunction) - Static method in class org.encog.neural.freeform.FreeformNetwork
-
Construct an Elmann recurrent neural network.
- createEvent(BayesianEvent) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Create, or register, the specified event with this bayesian network.
- createEvent(String, List<BayesianChoice>) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Create an event specified on the label and options provided.
- createEvent(String, String...) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Create the specified events based on a variable number of options, or choices.
- createFeedforward(int, int, int, int, ActivationFunction) - Static method in class org.encog.neural.freeform.FreeformNetwork
-
Create a feedforward freeform neural network.
- createFunction(String) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Create a function.
- createFunctionCall(EncogProgramNode, String, String) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Create a function call.
- createFunctionCall(String, String, String) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Create a function call.
- createHiddenNode() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- createInputLayer(int) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Create the input layer.
- createInputNode() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- createInputStream(String) - Static method in class org.encog.util.ResourceLoader
-
Create an input stream to read from the resource.
- createKey(String, int) - Static method in enum org.encog.ml.prg.extension.EncogOpcodeRegistry
-
Construct a lookup key for the hash map.
- createLayer(int) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Create a hidden layer.
- createLink(SubstrateNode, SubstrateNode) - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- createLink(NEATGenome, long, long, double) - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
Create a link between two neuron id's.
- createMainFunction() - Method in class org.encog.app.generate.program.EncogProgramNode
-
Create a new main function.
- createMethod() - Method in class org.encog.ml.model.EncogModel
-
Create the selected method.
- createMethod(String, String, int, int) - Method in interface org.encog.plugin.EncogPluginService1
-
Create a new machine learning method.
- createMethod(String, String, int, int) - Method in class org.encog.plugin.system.SystemActivationPlugin
-
Create a new machine learning method.
- createMethod(String, String, int, int) - Method in class org.encog.plugin.system.SystemMethodsPlugin
-
Create a new machine learning method.
- createMethod(String, String, int, int) - Method in class org.encog.plugin.system.SystemTrainingPlugin
-
- createML(int, int) - Method in interface org.encog.ensemble.EnsembleMLMethodFactory
-
- createML(int, int) - Method in class org.encog.ensemble.ml.mlp.factory.MultiLayerPerceptronFactory
-
- createNetworkFunction(String, File) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Create a new network function.
- createNewDistribution() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- createNode(Random, EncogProgram, int, List<ValueType>) - Method in class org.encog.ml.prg.generator.PrgFullGenerator
-
Create a random node for an Encog Program.
- createNode(Random, EncogProgram, int, List<ValueType>) - Method in interface org.encog.ml.prg.generator.PrgGenerator
-
Create a random node for an Encog Program.
- createNode(Random, EncogProgram, int, List<ValueType>) - Method in class org.encog.ml.prg.generator.PrgGrowGenerator
-
Create a random node for an Encog Program.
- createNode(Random, EncogProgram, int, List<ValueType>) - Method in class org.encog.ml.prg.generator.RampedHalfAndHalf
-
Create a random node for an Encog Program.
- createNode() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- createNumericOperators(EncogProgramContext) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add the opcodes for numeric operations to a context, do not use protected
division.
- createNumericOperators(EncogProgramContext, boolean) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add the opcodes for numeric operations to a context.
- createOutputLayer(int) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Create the output layer.
- createOutputNode() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- createPair(int, int) - Static method in class org.encog.ml.data.basic.BasicMLDataPair
-
Create a new data pair object of the correct size for the machine
learning method that is being trained.
- createParams(FlatNetwork) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Create an array of doubles to hold the specified flat network.
- createPoint(Date) - Method in class org.encog.ml.data.market.MarketMLDataSet
-
Create a datapoint at the specified date.
- createPoint(Date) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Create a temporal point from a time.
- createPoint(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Create a temporal data point using a sequence number.
- createProgram(String) - Method in class org.encog.ml.prg.EncogProgramContext
-
Create a new program, using this context.
- createRandomNode(Random, EncogProgram, int, List<ValueType>, boolean, boolean) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Create a random note according to the specified paramaters.
- createRowMatrix(double[]) - Static method in class org.encog.mathutil.matrices.Matrix
-
Turn an array of doubles into a row matrix.
- createSpecies() - Method in class org.encog.ml.ea.population.BasicPopulation
-
Create a species.
- createSpecies() - Method in interface org.encog.ml.ea.population.Population
-
Create a species.
- createStringFunctions(EncogProgramContext) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add the opcodes for string operations to a context.
- createTaskGroup() - Method in class org.encog.util.concurrency.EngineConcurrency
-
Create a new task group.
- createTerminalNode(Random, EncogProgram, List<ValueType>) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Create a terminal node.
- createTrainer(boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
-
Create a trainer to use.
- createTrainer(boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
-
Create a trainer to use.
- createTrainer(boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
Create a trainer to use.
- createTraining(MLMethod, MLDataSet, String, String) - Method in interface org.encog.plugin.EncogPluginService1
-
Create a trainer.
- createTraining(MLMethod, MLDataSet, String, String) - Method in class org.encog.plugin.system.SystemActivationPlugin
-
Create a trainer.
- createTraining(MLMethod, MLDataSet, String, String) - Method in class org.encog.plugin.system.SystemMethodsPlugin
-
Create a trainer.
- createTraining(MLMethod, MLDataSet, String, String) - Method in class org.encog.plugin.system.SystemTrainingPlugin
-
- createTrigFunctions(EncogProgramContext) - Static method in class org.encog.ml.prg.extension.StandardExtensions
-
Add the opcodes for trig functions operations to a context.
- CrossTraining - Class in org.encog.neural.networks.training.cross
-
Base class for cross training trainers.
- CrossTraining(MLMethod, FoldedDataSet) - Constructor for class org.encog.neural.networks.training.cross.CrossTraining
-
Construct a cross trainer.
- crossvalidate(int, boolean) - Method in class org.encog.ml.model.EncogModel
-
Crossvalidate and fit.
- CrossValidationKFold - Class in org.encog.neural.networks.training.cross
-
Train using K-Fold cross validation.
- CrossValidationKFold(MLTrain, int) - Constructor for class org.encog.neural.networks.training.cross.CrossValidationKFold
-
Construct a cross validation trainer.
- CSVDataCODEC - Class in org.encog.ml.data.buffer.codec
-
A CODEC used to read/write data from/to a CSV data file.
- CSVDataCODEC(File, CSVFormat, boolean) - Constructor for class org.encog.ml.data.buffer.codec.CSVDataCODEC
-
Constructor to create CSV from binary..
- CSVDataCODEC(File, CSVFormat, boolean, int, int, boolean) - Constructor for class org.encog.ml.data.buffer.codec.CSVDataCODEC
-
Create a CODEC to load data from CSV to binary.
- CSVDataSource - Class in org.encog.ml.data.versatile.sources
-
Allow a CSV file to serve as a source for the versatile data source.
- CSVDataSource(File, boolean, char) - Constructor for class org.encog.ml.data.versatile.sources.CSVDataSource
-
Construct a CSV source from a filename.
- CSVDataSource(File, boolean, CSVFormat) - Constructor for class org.encog.ml.data.versatile.sources.CSVDataSource
-
Construct a CSV source from a filename.
- CSVError - Exception in org.encog.util.csv
-
An error has occured while working with CSV data.
- CSVError(String) - Constructor for exception org.encog.util.csv.CSVError
-
Construct a message exception.
- CSVError(Throwable) - Constructor for exception org.encog.util.csv.CSVError
-
Construct an exception that holds another exception.
- CSVFormat - Class in org.encog.util.csv
-
Specifies a CSV format.
- CSVFormat() - Constructor for class org.encog.util.csv.CSVFormat
-
By default use USA conventions.
- CSVFormat(char, char) - Constructor for class org.encog.util.csv.CSVFormat
-
Construct a CSV format with he specified decimal and separator
characters.
- CSVHeaders - Class in org.encog.app.analyst.util
-
Utility class to help deal with CSV headers.
- CSVHeaders(File, boolean, CSVFormat) - Constructor for class org.encog.app.analyst.util.CSVHeaders
-
Construct the object.
- CSVHeaders(List<String>) - Constructor for class org.encog.app.analyst.util.CSVHeaders
-
Construct the object.
- CSVHeaders(String[]) - Constructor for class org.encog.app.analyst.util.CSVHeaders
-
Construct the object.
- CSVNeuralDataSet - Class in org.encog.ml.data.specific
-
An implementation of the NeuralDataSet interface designed to provide a CSV
file to the neural network.
- CSVNeuralDataSet(String, int, int, boolean) - Constructor for class org.encog.ml.data.specific.CSVNeuralDataSet
-
Construct this data set using a comma as a delimiter.
- CSVNeuralDataSet(String, int, int, boolean, CSVFormat, boolean) - Constructor for class org.encog.ml.data.specific.CSVNeuralDataSet
-
Construct this data set using a comma as a delimiter.
- CUT - Static variable in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
The cutoff for random data.
- CYCLES - Static variable in class org.encog.ml.factory.MLTrainFactory
-
The number of cycles.
- DATA - Static variable in class org.encog.persist.PersistConst
-
Data.
- DATA_CONFIG_GOAL - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "DATA:CONFIG_goal".
- DataDivision - Class in org.encog.ml.data.versatile.division
-
A division of data inside of a versatile data set.
- DataDivision(double) - Constructor for class org.encog.ml.data.versatile.division.DataDivision
-
Construct a division.
- DataField - Class in org.encog.app.analyst.script
-
Holds stats on a data field for the Encog Analyst.
- DataField(String) - Constructor for class org.encog.app.analyst.script.DataField
-
Construct the data field.
- DataFold - Class in org.encog.ml.data.cross
-
- DataFold(MatrixMLDataSet, MatrixMLDataSet) - Constructor for class org.encog.ml.data.cross.DataFold
-
- DataNormalization - Class in org.encog.util.normalize
-
This class is used to normalize both input and ideal data for neural
networks.
- DataNormalization() - Constructor for class org.encog.util.normalize.DataNormalization
-
- DataSetCODEC - Interface in org.encog.ml.data.buffer.codec
-
A CODEC is used to encode and decode data.
- dataSetFactory - Variable in class org.encog.ensemble.Ensemble
-
- dataSetSize - Variable in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- dataSource - Variable in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- DataUnit - Class in org.encog.bot.dataunit
-
Data units are very abstract pieces of data that the browser processes.
- DataUnit() - Constructor for class org.encog.bot.dataunit.DataUnit
-
- DATE - Static variable in class org.encog.app.analyst.csv.basic.FileData
-
The date.
- date2Long(Date) - Static method in class org.encog.util.time.NumericDateUtil
-
- DateUtil - Class in org.encog.util.time
-
Simple date utility class.
- DAYS_WEEK - Static variable in class org.encog.util.time.TimeSpan
-
Days in a week.
- decay(double) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Called to decay the learning rate and radius by the specified amount.
- decay(double, double) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Decay the learning rate and radius by the specified amount.
- DECIMAL_COMMA - Static variable in class org.encog.util.csv.CSVFormat
-
Use a decimal comma, and a semicolon to separate numbers.
- DECIMAL_POINT - Static variable in class org.encog.util.csv.CSVFormat
-
Use a decimal point, and a comma to separate numbers.
- decode(boolean, boolean, double[], MLData) - Method in class org.encog.app.analyst.util.AnalystUtility
-
Decode fields, using the analyst.
- decode(double[]) - Method in class org.encog.mathutil.Equilateral
-
Decode a set of activations and see which set it has the lowest Euclidean
distance from.
- decode(Genome) - Method in interface org.encog.ml.ea.codec.GeneticCODEC
-
Decode the specified genome into a phenome.
- decode(Genome) - Method in class org.encog.ml.ea.codec.GenomeAsPhenomeCODEC
-
Decode the specified genome into a phenome.
- decode(Genome) - Method in class org.encog.ml.genetic.MLEncodableCODEC
-
Decode the specified genome into a phenome.
- decode() - Method in class org.encog.ml.genetic.MLMethodGenome
-
Decode the phenotype.
- decode(Genome) - Method in class org.encog.ml.prg.PrgCODEC
-
Decode the specified genome into a phenome.
- decode(Genome) - Method in class org.encog.neural.hyperneat.HyperNEATCODEC
-
Decode the specified genome into a phenome.
- decode(NEATPopulation, Substrate, Genome) - Method in class org.encog.neural.hyperneat.HyperNEATCODEC
-
- decode(Genome) - Method in class org.encog.neural.neat.NEATCODEC
-
Decode the specified genome into a phenome.
- DECODE - Static variable in class org.encog.util.text.Base64
-
Specify decoding in first bit.
- decode(byte[]) - Static method in class org.encog.util.text.Base64
-
Low-level access to decoding ASCII characters in
the form of a byte array.
- decode(byte[], int, int, int) - Static method in class org.encog.util.text.Base64
-
Low-level access to decoding ASCII characters in
the form of a byte array.
- decode(String) - Static method in class org.encog.util.text.Base64
-
Decodes data from Base64 notation, automatically
detecting gzip-compressed data and decompressing it.
- decode(String, int) - Static method in class org.encog.util.text.Base64
-
Decodes data from Base64 notation, automatically
detecting gzip-compressed data and decompressing it.
- decodeFileToFile(String, String) - Static method in class org.encog.util.text.Base64
-
Reads infile and decodes it to outfile.
- decodeFromArray(double[]) - Method in interface org.encog.ml.MLEncodable
-
Decode an array to this object.
- decodeFromArray(double[]) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Decode an array to this object.
- decodeFromArray(double[]) - Method in class org.encog.neural.networks.BasicNetwork
-
Decode an array to this object.
- decodeFromArray(double[]) - Method in class org.encog.neural.rbf.RBFNetwork
-
Decode an array to this object.
- decodeFromFile(String) - Static method in class org.encog.util.text.Base64
-
Convenience method for reading a base64-encoded
file and decoding it.
- decodeNetwork(double[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Decode the specified data into the weights of the neural network.
- decodeToFile(String, String) - Static method in class org.encog.util.text.Base64
-
Convenience method for decoding data to a file.
- decodeToObject(String) - Static method in class org.encog.util.text.Base64
-
Attempts to decode Base64 data and deserialize a Java
Object within.
- decodeToObject(String, int, ClassLoader) - Static method in class org.encog.util.text.Base64
-
Attempts to decode Base64 data and deserialize a Java
Object within.
- decreaseLevel() - Method in class org.encog.ml.prg.opp.LevelHolder
-
Decrease the level.
- decreaseTemperature(double) - Method in class org.encog.neural.thermal.BoltzmannMachine
-
Decrease the temperature by the specified amount.
- deepCopy(Object) - Static method in class org.encog.util.obj.ObjectCloner
-
Perform a deep copy.
- DEFAULT_ALTERNATE_CYCLES - Static variable in class org.encog.ml.train.strategy.HybridStrategy
-
The default number of cycles to use the alternate training for.
- DEFAULT_BIAS_ACTIVATION - Static variable in class org.encog.neural.flat.FlatNetwork
-
The default bias activation.
- DEFAULT_BUFFER_SIZE - Static variable in class org.encog.app.analyst.csv.shuffle.ShuffleCSV
-
The default buffer size.
- DEFAULT_C - Static variable in class org.encog.ml.svm.SVM
-
The default C.
- DEFAULT_CACHE_SIZE - Static variable in class org.encog.ml.svm.SVM
-
The default cache size.
- DEFAULT_COEF0 - Static variable in class org.encog.ml.svm.SVM
-
The default COEF0.
- DEFAULT_CONNECTION_LIMIT - Static variable in class org.encog.neural.networks.BasicNetwork
-
The default connection limit.
- DEFAULT_CONST_BEGIN - Static variable in class org.encog.ml.svm.training.SVMSearchTrain
-
The default starting number for C.
- DEFAULT_CONST_END - Static variable in class org.encog.ml.svm.training.SVMSearchTrain
-
The default ending number for C.
- DEFAULT_CONST_STEP - Static variable in class org.encog.ml.svm.training.SVMSearchTrain
-
The default step for C.
- DEFAULT_CYCLES - Static variable in class org.encog.neural.neat.NEATPopulation
-
Default number of activation cycles.
- DEFAULT_DEGREE - Static variable in class org.encog.ml.svm.SVM
-
The default degree.
- DEFAULT_DOUBLE_EQUAL - Static variable in class org.encog.Encog
-
Default point at which two doubles are equal.
- DEFAULT_ENCODING - Static variable in class org.encog.Encog
-
The default encoding used by Encog.
- DEFAULT_EPS - Static variable in class org.encog.ml.svm.SVM
-
The default EPS.
- DEFAULT_EVAL_PERCENT - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The default evaluation percent.
- DEFAULT_GAMMA_BEGIN - Static variable in class org.encog.ml.svm.training.SVMSearchTrain
-
The default gamma begin.
- DEFAULT_GAMMA_END - Static variable in class org.encog.ml.svm.training.SVMSearchTrain
-
The default gamma end.
- DEFAULT_GAMMA_STEP - Static variable in class org.encog.ml.svm.training.SVMSearchTrain
-
The default gamma step.
- DEFAULT_INC - Static variable in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
Default inc.
- DEFAULT_INITIAL_UPDATE - Static variable in class org.encog.neural.networks.training.propagation.resilient.RPROPConst
-
The starting update for a delta.
- DEFAULT_ITERATIONS - Static variable in class org.encog.app.analyst.commands.CmdCluster
-
The default number of iterations.
- DEFAULT_MAX_CLASS - Static variable in class org.encog.app.analyst.script.AnalystScript
-
The default MAX size for a class.
- DEFAULT_MAX_ERROR - Static variable in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
The default max error.
- DEFAULT_MAX_STEP - Static variable in class org.encog.neural.networks.training.propagation.resilient.RPROPConst
-
The maximum amount a delta can reach.
- DEFAULT_MIN_IMPROVEMENT - Static variable in class org.encog.ml.train.strategy.HybridStrategy
-
The default minimum improvement before we switch to the alternate
training method.
- DEFAULT_MIN_IMPROVEMENT - Static variable in class org.encog.ml.train.strategy.StopTrainingStrategy
-
The default minimum improvement before training stops.
- DEFAULT_MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
The default minimum improvement before stop.
- DEFAULT_MOD1 - Static variable in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
First part of default mod.
- DEFAULT_MOD2 - Static variable in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
Second part of default mod.
- DEFAULT_MULT - Static variable in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
Default mult.
- DEFAULT_NU - Static variable in class org.encog.ml.svm.SVM
-
The default NU.
- DEFAULT_NUM_SIGMAS - Static variable in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
The default number of sigmas to evaluate between the low and high.
- DEFAULT_P - Static variable in class org.encog.ml.svm.SVM
-
The default P.
- DEFAULT_PRECISION - Static variable in class org.encog.Encog
-
The default precision to use for compares.
- DEFAULT_SAMPLE_SIZE - Static variable in class org.encog.ml.bayesian.query.sample.SamplingQuery
-
The default sample size.
- DEFAULT_SIGMA_HIGH - Static variable in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
The default sigma high value.
- DEFAULT_SIGMA_LOW - Static variable in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
THe default sigma low value.
- DEFAULT_SURVIVAL_RATE - Static variable in class org.encog.neural.neat.NEATPopulation
-
The default survival rate.
- DEFAULT_TOLERATE_CYCLES - Static variable in class org.encog.ml.train.strategy.HybridStrategy
-
The default number of cycles to tolerate bad improvement for.
- DEFAULT_TOLERATE_CYCLES - Static variable in class org.encog.ml.train.strategy.StopTrainingStrategy
-
The default number of cycles to tolerate.
- DEFAULT_TRAIN_ERROR - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The default training error.
- DEFAULT_TRAIN_PERCENT - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The default training percent.
- DEFAULT_ZERO_TOLERANCE - Static variable in class org.encog.neural.networks.training.propagation.resilient.RPROPConst
-
The default zero tolerance.
- defineClass(String, FieldDirection, NormalizationAction, List<ClassItem>) - Method in class org.encog.app.analyst.script.AnalystScript
-
- defineClass(String) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
Define a class for a catagorical value.
- defineClass(String[]) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
Define an array of classes for a catagorical value.
- defineClassificationStructure(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Define a classification structure of the form P(A|B) = P(C)
- defineConst(EncogArgType, String, String) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Define a const.
- defineEventType(BayesianEvent, EventType) - Method in class org.encog.ml.bayesian.query.BasicQuery
-
Define an event type to be either hidden(default), evidence(input) or
outcome (output).
- defineEventType(BayesianEvent, EventType) - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
Define an event type to be either hidden(default), evidence(input) or
outcome (output).
- defineField(String, FieldDirection, NormalizationAction, double, double) - Method in class org.encog.app.analyst.script.AnalystScript
-
- defineInput(ColumnDefinition) - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Define an input column.
- defineMissingHandler(ColumnDefinition, MissingHandler) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Define a missing value handler.
- defineOutput(ColumnDefinition) - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Define an output column.
- defineProbability(String, double) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Define the probability for an event.
- defineProbability(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Define a probability.
- defineRelationship(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Define a relationship.
- defineRelationships(BayesianNetwork) - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
Define the relationships.
- defineSingleOutputOthersInput(ColumnDefinition) - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Define a single column as an output column, all others as inputs.
- defineSourceColumn(String, int, ColumnType) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Define a source column.
- defineSourceColumn(String, int, ColumnType) - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Define a source column.
- defineSourceColumn(String, ColumnType) - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Define a source column.
- defineTruthTable(BayesianNetwork, double) - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
Define the truth table.
- defineUnknownValue(String) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Define the string that signifies an unknown value (eg "?")
- defineVariable(String) - Method in class org.encog.ml.prg.EncogProgramContext
-
Define the specified variable as floating point.
- defineVariable(String, ValueType) - Method in class org.encog.ml.prg.EncogProgramContext
-
Define the specified variable as the specified type.
- defineVariable(String, ValueType, int, int) - Method in class org.encog.ml.prg.EncogProgramContext
-
Define a variable.
- defineVariable(VariableMapping) - Method in class org.encog.ml.prg.EncogProgramContext
-
Define a variable, based on a mapping.
- defineVariable(VariableMapping) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Define the specified variable mapping.
- deg2rad(double) - Static method in class org.encog.mathutil.EncogMath
-
Convert degrees to radians.
- DEG_CIRCLE - Static variable in class org.encog.mathutil.MathConst
-
Degrees in a circle.
- DEG_SEMICIRCLE - Static variable in class org.encog.mathutil.MathConst
-
Degrees in a semicircle.
- degree - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- deleteCol(Matrix, int) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Delete one column from the matrix.
- deleteCol(int) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Delete a column.
- deleteDirectory(File) - Static method in class org.encog.util.file.Directory
-
Delete a directory and all children.
- deleteRow(Matrix, int) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Delete a row from the matrix.
- deleteRow(int) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Delete a row.
- DELTA_MIN - Static variable in class org.encog.neural.networks.training.propagation.resilient.RPROPConst
-
The minimum delta value for a weight matrix value.
- deNormalize(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Denormalize the specified value.
- deNormalize(double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Denormalize the specified value.
- denormalizeColumn(ColumnDefinition, MLData, int) - Method in class org.encog.ml.data.versatile.normalizers.IndexedNormalizer
-
Denormalize a value.
- denormalizeColumn(ColumnDefinition, MLData, int) - Method in interface org.encog.ml.data.versatile.normalizers.Normalizer
-
Denormalize a value.
- denormalizeColumn(ColumnDefinition, MLData, int) - Method in class org.encog.ml.data.versatile.normalizers.OneOfNNormalizer
-
Denormalize a value.
- denormalizeColumn(ColumnDefinition, MLData, int) - Method in class org.encog.ml.data.versatile.normalizers.PassThroughNormalizer
-
Denormalize a value.
- denormalizeColumn(ColumnDefinition, MLData, int) - Method in class org.encog.ml.data.versatile.normalizers.RangeNormalizer
-
Denormalize a value.
- denormalizeColumn(ColumnDefinition, MLData, int) - Method in class org.encog.ml.data.versatile.normalizers.RangeOrdinal
-
Denormalize a value.
- denormalizeColumn(ColumnDefinition, boolean, MLData, int) - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Normalize a column, with a double input.
- denormalizeColumn(ColumnDefinition, boolean, MLData, int) - Method in interface org.encog.ml.data.versatile.normalizers.strategies.NormalizationStrategy
-
Normalize a column, with a double input.
- denormalizeOutputVectorToString(MLData) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Denormalize a complete output vector to an array of strings.
- DEPTH - Static variable in class org.encog.persist.PersistConst
-
Depth.
- DepthFirstSearch - Class in org.encog.ml.graph.search
-
- DepthFirstSearch(BasicGraph, BasicNode, SearchGoal) - Constructor for class org.encog.ml.graph.search.DepthFirstSearch
-
- DepthFirstTraversal - Class in org.encog.ml.tree.traverse
-
Performs a depth-first traversal.
- DepthFirstTraversal() - Constructor for class org.encog.ml.tree.traverse.DepthFirstTraversal
-
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationBiPolar
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationClippedLinear
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationCompetitive
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationElliott
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationElliottSymmetric
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in interface org.encog.engine.network.activation.ActivationFunction
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationGaussian
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationLinear
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationLOG
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationRamp
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationSigmoid
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationSIN
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationSoftMax
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationSteepenedSigmoid
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationStep
-
Calculate the derivative.
- derivativeFunction(double, double) - Method in class org.encog.engine.network.activation.ActivationTANH
-
Calculate the derivative.
- DeriveMinimum - Class in org.encog.neural.networks.training.pnn
-
This class determines optimal values for multiple sigmas in a PNN kernel.
- DeriveMinimum() - Constructor for class org.encog.neural.networks.training.pnn.DeriveMinimum
-
- DESCRIPTION - Static variable in class org.encog.persist.PersistConst
-
A description.
- det() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Determinant
- detectPerformers() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Detect performers.
- detectPerformers(boolean) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Detect performers.
- determinant(Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
- determineActionState(GridState, Action) - Method in class org.encog.ml.world.grid.probability.GridAbstractProbability
-
- determineActionToState(GridState, GridState) - Method in class org.encog.ml.world.grid.GridWorld
-
- determineArgumentTypes(List<ValueType>) - Method in class org.encog.ml.prg.extension.ParamTemplate
-
Determine the possable argument types, given the parent types.
- determineBestSpecies() - Method in class org.encog.ml.ea.population.BasicPopulation
-
Determine which species has the top genome.
- determineBestSpecies() - Method in interface org.encog.ml.ea.population.Population
-
Determine which species has the top genome.
- determineClass(double[]) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Determine what class the specified data belongs to.
- determineClass(int, double[]) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Determine the class using part of an array.
- determineClass(double[]) - Method in class org.encog.util.arrayutil.NormalizedField
-
Determine what class the specified data belongs to.
- determineClasses(MLData) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Determine the classes for the specified input.
- determineCost(World, State, Action) - Method in interface org.encog.ml.world.PerformAction
-
- determineFormat() - Method in class org.encog.app.analyst.script.AnalystScript
-
Determine the output format.
- determineInputCount() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine the input count.
- determineInputFieldCount() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine the input field count, the fields are higher-level
than columns.
- determineMaxDepth(Random) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- determineMaxDepth(Random) - Method in class org.encog.ml.prg.generator.RampedHalfAndHalf
- determineMaxTimeSlice() - Method in class org.encog.app.analyst.EncogAnalyst
-
- determineMinTimeSlice() - Method in class org.encog.app.analyst.EncogAnalyst
-
- determineMode(EncogAnalyst) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Determine the mode, this is the class item that has the most instances.
- determineNeuronSignificance(int, int) - Method in class org.encog.neural.prune.PruneSelective
-
Determine the significance of the neuron.
- determineNextAction(WorldAgent) - Method in interface org.encog.ml.world.AgentPolicy
-
- determineNodeType(ProgramNode) - Method in class org.encog.parse.expression.CommonRender
-
- determineNodeType(ProgramNode) - Method in class org.encog.parse.expression.latex.RenderLatexExpression
-
- determineOutputCount() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine the output count, this is the number of output
columns needed.
- determineOutputCount(VersatileMLDataSet) - Method in class org.encog.ml.model.config.FeedforwardConfig
-
Determine the needed output count.
- determineOutputCount(VersatileMLDataSet) - Method in interface org.encog.ml.model.config.MethodConfig
-
Determine the needed output count.
- determineOutputCount(VersatileMLDataSet) - Method in class org.encog.ml.model.config.NEATConfig
-
Determine the needed output count.
- determineOutputCount(VersatileMLDataSet) - Method in class org.encog.ml.model.config.PNNConfig
-
Determine the needed output count.
- determineOutputCount(VersatileMLDataSet) - Method in class org.encog.ml.model.config.RBFNetworkConfig
-
Determine the needed output count.
- determineOutputCount(VersatileMLDataSet) - Method in class org.encog.ml.model.config.SVMConfig
-
- determineOutputFieldCount() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine the number of output fields.
- determineResultingAction(GridState, GridState) - Method in class org.encog.ml.world.grid.probability.GridAbstractProbability
-
- determineSuccessorStates(State, Action) - Method in interface org.encog.ml.world.ActionProbability
-
- determineSuccessorStates(State, Action) - Method in class org.encog.ml.world.grid.probability.GridDeterministicProbability
-
- determineSuccessorStates(State, Action) - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- determineTotalColumns() - Method in class org.encog.app.analyst.EncogAnalyst
-
- determineTotalInputFieldCount() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine the total input field count, minus ignored fields.
- determineUniqueColumns() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine how many unique columns there are.
- determineUniqueInputFieldCount() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine the unique input field count.
- determineUniqueOutputFieldCount() - Method in class org.encog.app.analyst.EncogAnalyst
-
Determine the unique output field count.
- DetermineWorkload - Class in org.encog.util.concurrency
-
Used by several Encog training methods to break up a workload.
- DetermineWorkload(int, int) - Constructor for class org.encog.util.concurrency.DetermineWorkload
-
Determine the workload.
- DimensionConstraint - Class in org.encog.mathutil.dimension
-
Specifies a constraint for dimensions, using a lower and upper bound.
- DimensionConstraint(int, int, int) - Constructor for class org.encog.mathutil.dimension.DimensionConstraint
-
Construct the constraint.
- Directory - Class in org.encog.util.file
-
Directory utilities.
- DiscardMissing - Class in org.encog.app.analyst.missing
-
Handle missing values by discarding them.
- DiscardMissing() - Constructor for class org.encog.app.analyst.missing.DiscardMissing
-
- DiscreteCell - Interface in org.encog.ca.universe
-
- DiscreteDistribution - Class in org.encog.ml.hmm.distributions
-
A discrete distribution is a distribution with a finite set of states that it
can be in.
- DiscreteDistribution(double[][]) - Constructor for class org.encog.ml.hmm.distributions.DiscreteDistribution
-
Construct a discrete distribution with the specified probabilities.
- DiscreteDistribution(int[]) - Constructor for class org.encog.ml.hmm.distributions.DiscreteDistribution
-
Construct a discrete distribution.
- displayDate(Date) - Static method in class org.encog.util.csv.ReadCSV
-
Format a date.
- distance(MLData) - Method in class org.encog.ml.data.basic.BasicMLDataCentroid
-
The distance between this centroid and an element.
- distance(MLDataPair) - Method in class org.encog.ml.data.basic.BasicMLDataPairCentroid
-
The distance between this centroid and an element.
- distance(EuclideanNode, EuclideanNode) - Static method in class org.encog.ml.graph.EuclideanNode
-
- distance(HiddenMarkovModel, HiddenMarkovModel) - Method in class org.encog.ml.hmm.alog.KullbackLeiblerDistanceCalculator
-
- distance(O) - Method in interface org.encog.util.kmeans.Centroid
-
The distance between this centroid and an element.
- Distort - Class in org.encog.mathutil.randomize
-
A randomizer that distorts what is already present in the neural network.
- Distort(double) - Constructor for class org.encog.mathutil.randomize.Distort
-
Construct a distort randomizer for the specified factor.
- Div - Class in org.encog.bot.browse.range
-
A document range that represents the beginning and ending DIV tag, as well as
any tages embedded between them.
- Div(WebPage) - Constructor for class org.encog.bot.browse.range.Div
-
Construct a range to hold the DIV tag.
- div(ComplexNumber) - Method in class org.encog.mathutil.ComplexNumber
-
Division of Complex numbers (doesn't change this Complex number).
- div(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform a division on two expression values.
- div() - Method in class org.encog.util.datastruct.StackInt
-
- divide(Matrix, double) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Return a matrix with each cell divided by the specified value.
- divide(List<DataDivision>, boolean, GenerateRandom) - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Divide, and optionally shuffle, the dataset.
- DivisionByZeroError - Exception in org.encog.ml.prg.expvalue
-
A division by zero.
- DivisionByZeroError() - Constructor for exception org.encog.ml.prg.expvalue.DivisionByZeroError
-
- DivisionByZeroError(String) - Constructor for exception org.encog.ml.prg.expvalue.DivisionByZeroError
-
Just a message.
- DivisionByZeroError(String, Throwable) - Constructor for exception org.encog.ml.prg.expvalue.DivisionByZeroError
-
Message with a throwable.
- DivisionByZeroError(Throwable) - Constructor for exception org.encog.ml.prg.expvalue.DivisionByZeroError
-
Just a throwable.
- DO_BREAK_LINES - Static variable in class org.encog.util.text.Base64
-
Do break lines when encoding.
- DocumentRange - Class in org.encog.bot.browse.range
-
Base class that represents a document range.
- DocumentRange(WebPage) - Constructor for class org.encog.bot.browse.range.DocumentRange
-
Construct a document range from the specified WebPage.
- DONT_GUNZIP - Static variable in class org.encog.util.text.Base64
-
Specify that gzipped data should not be automatically gunzipped.
- dotForm(String, String, String) - Static method in class org.encog.app.analyst.script.prop.PropertyEntry
-
Put a property in dot form, which is "section.subsection.name".
- dotProduct(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Compute the dot product for the two matrixes.
- dotProduct(double[], double[]) - Method in class org.encog.mathutil.VectorAlgebra
-
Take the dot product of two vectors.
- double2bipolar(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert a bipolar value to a boolean.
- double2bipolar(double[]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert a bipolar array to booleans.
- double2bipolar(double[][]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert a bipolar array to a boolean array.
- DOUBLE_SIZE - Static variable in class org.encog.ml.data.buffer.EncogEGBFile
-
The size of a double.
- DoubleArrayGenome - Class in org.encog.ml.genetic.genome
-
A genome made up of continuous doubles.
- DoubleArrayGenome(int) - Constructor for class org.encog.ml.genetic.genome.DoubleArrayGenome
-
Construct a genome of a specific size.
- DoubleArrayGenome(DoubleArrayGenome) - Constructor for class org.encog.ml.genetic.genome.DoubleArrayGenome
-
Construct a genome based on another genome.
- DoubleArrayGenomeFactory - Class in org.encog.ml.genetic.genome
-
A factory that creates DoubleArrayGenome objects of a specific size.
- DoubleArrayGenomeFactory(int) - Constructor for class org.encog.ml.genetic.genome.DoubleArrayGenomeFactory
-
Construct the genome factory.
- doubleEquals(double, double) - Static method in class org.encog.mathutil.EncogMath
-
Determine if one double equals another, within the default percision.
- DoubleString - Class in org.encog.util.text
-
- DoubleString() - Constructor for class org.encog.util.text.DoubleString
-
- doubleToObject(double[]) - Static method in class org.encog.util.EngineArray
-
Convert an array of double primitives to Double objects.
- download() - Method in class org.encog.app.analyst.EncogAnalyst
-
Download a raw file from the Internet.
- downloadPage(URL, File) - Static method in class org.encog.bot.BotUtil
-
Load the specified URL to a file.
- downsample(Downsample, boolean, int, int, double, double) - Method in class org.encog.platformspecific.j2se.data.image.ImageMLData
-
Downsample, and copy, the image contents into the data of this object.
- downsample(int, int) - Method in class org.encog.platformspecific.j2se.data.image.ImageMLDataSet
-
Downsample all images and generate training data.
- Downsample - Interface in org.encog.util.downsample
-
Utility to downsample an image.
- downSample(Image, int, int) - Method in interface org.encog.util.downsample.Downsample
-
Downsample the image to the specified height and width.
- downSample(Image, int, int) - Method in class org.encog.util.downsample.RGBDownsample
-
Called to downsample the image and store it in the down sample component.
- downSample(Image, int, int) - Method in class org.encog.util.downsample.SimpleIntensityDownsample
-
Called to downsample the image and store it in the down sample component.
- downSampleRegion(int, int) - Method in class org.encog.util.downsample.RGBDownsample
-
Called to downsample a region of the image.
- dump() - Method in class org.encog.ml.schedule.ScheduleGraph
-
- dumpArray(double[]) - Static method in class org.encog.util.logging.DumpMatrix
-
Dump an array of numbers to a string.
- dumpAsCommonExpression() - Method in class org.encog.ml.prg.EncogProgram
-
- dumpCounts() - Method in class org.encog.app.analyst.csv.balance.BalanceCSV
-
Return a string that lists the counts per class.
- dumpCounts() - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
- dumpCurrentState() - Method in class org.encog.ml.bayesian.query.sample.SamplingQuery
-
- DumpMatrix - Class in org.encog.util.logging
-
A utility for writing matrixes to the log.
- dumpMatrix(Matrix) - Static method in class org.encog.util.logging.DumpMatrix
-
Dump a matrix to a string.
- dumpMembers(int) - Method in class org.encog.ml.prg.train.PrgPopulation
-
Dump the specified number of genomes.
- dumpNode(StringBuilder, ActionNode, Map<ActionNode, ActionNode>) - Method in class org.encog.ml.schedule.ScheduleGraph
-
- dumpWeights() - Method in class org.encog.neural.networks.BasicNetwork
-
- EACompileError - Exception in org.encog.ml.ea.exception
-
The genome has generated a compile error and is invalid.
- EACompileError(String) - Constructor for exception org.encog.ml.ea.exception.EACompileError
-
Construct the error.
- EACompileError(String, Throwable) - Constructor for exception org.encog.ml.ea.exception.EACompileError
-
Construct the error.
- EACompileError(Throwable) - Constructor for exception org.encog.ml.ea.exception.EACompileError
-
Construct the error.
- EAError - Exception in org.encog.ml.ea.exception
-
A general evolutionary algorithm error.
- EAError(String) - Constructor for exception org.encog.ml.ea.exception.EAError
-
Construct the exception.
- EAError(String, Throwable) - Constructor for exception org.encog.ml.ea.exception.EAError
-
Construct the exception.
- EAError(Throwable) - Constructor for exception org.encog.ml.ea.exception.EAError
-
Construct the exception.
- EarlyStoppingStrategy - Class in org.encog.ml.train.strategy.end
-
Stop early when validation set no longer improves.
- EarlyStoppingStrategy(MLDataSet, MLDataSet) - Constructor for class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
Construct the early stopping strategy.
- EarlyStoppingStrategy(MLDataSet, MLDataSet, int, double, double) - Constructor for class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
Construct the early stopping strategy.
- EARuntimeError - Exception in org.encog.ml.ea.exception
-
An error has occurred while running a phenotype (or genome).
- EARuntimeError(String) - Constructor for exception org.encog.ml.ea.exception.EARuntimeError
-
Construct an error.
- EARuntimeError(String, Throwable) - Constructor for exception org.encog.ml.ea.exception.EARuntimeError
-
Construct an error.
- EARuntimeError(Throwable) - Constructor for exception org.encog.ml.ea.exception.EARuntimeError
-
Construct an error.
- eatWhitespace() - Method in class org.encog.parse.tags.read.ReadTags
-
Remove any whitespace characters that are next in the InputStream.
- eatWhiteSpace() - Method in class org.encog.util.SimpleParser
-
- EAWorker - Class in org.encog.ml.ea.train.basic
-
A worker thread for an Evolutionary Algorithm.
- EAWorker(BasicEA, Species) - Constructor for class org.encog.ml.ea.train.basic.EAWorker
-
Construct the EA worker.
- EG_FORMAT - Static variable in class org.encog.util.csv.CSVFormat
-
EG files, internally use a decimal point and comma separator.
- EigenvalueDecomposition - Class in org.encog.mathutil.matrices.decomposition
-
Eigenvalues and eigenvectors of a real matrix.
- EigenvalueDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition
-
Check for symmetry, then construct the eigenvalue decomposition Structure
to access D and V.
- EIGHT_SPAN - Static variable in class org.encog.app.analyst.report.AnalystReport
-
Used as a col-span.
- ELEMENT_COUNT - Static variable in class org.encog.ca.universe.basic.BasicUniverse
-
- ElementaryCA - Class in org.encog.ca.program.elementary
-
- ElementaryCA(Universe, int) - Constructor for class org.encog.ca.program.elementary.ElementaryCA
-
- ElmanPattern - Class in org.encog.neural.pattern
-
This class is used to generate an Elman style recurrent neural network.
- ElmanPattern() - Constructor for class org.encog.neural.pattern.ElmanPattern
-
Create an object to generate Elman neural networks.
- embedTraining(File) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Embed training data.
- EmptyScoreFunction - Class in org.encog.ml.ea.score
-
An empty score function.
- EmptyScoreFunction() - Constructor for class org.encog.ml.ea.score.EmptyScoreFunction
-
- enableConnection(int, int, int, boolean) - Method in class org.encog.neural.networks.BasicNetwork
-
Enable, or disable, a connection.
- ENABLED - Static variable in class org.encog.persist.PersistConst
-
Enabled.
- encode(int) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Encode the class.
- encode(String) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Encode the string to numeric form.
- encode(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- encode(boolean, boolean, double[], MLData) - Method in class org.encog.app.analyst.util.AnalystUtility
-
Encode fields, using the analyst.
- encode(int) - Method in class org.encog.mathutil.Equilateral
-
Get the activations for the specified set.
- encode(MLMethod) - Method in interface org.encog.ml.ea.codec.GeneticCODEC
-
Attempt to build a genome from a phenome.
- encode(MLMethod) - Method in class org.encog.ml.ea.codec.GenomeAsPhenomeCODEC
-
Attempt to build a genome from a phenome.
- encode(MLMethod) - Method in class org.encog.ml.genetic.MLEncodableCODEC
-
Attempt to build a genome from a phenome.
- encode(MLMethod) - Method in class org.encog.ml.prg.PrgCODEC
-
Attempt to build a genome from a phenome.
- encode(MLDataSet, int) - Static method in class org.encog.ml.svm.training.EncodeSVMProblem
-
Encode the Encog dataset.
- encode(MLMethod) - Method in class org.encog.neural.hyperneat.HyperNEATCODEC
-
- encode(MLMethod) - Method in class org.encog.neural.neat.NEATCODEC
-
This method is not currently implemented.
- encode(String) - Static method in class org.encog.util.HTMLReport
-
- ENCODE - Static variable in class org.encog.util.http.FormUtility
-
The charset to use for URL encoding.
- ENCODE - Static variable in class org.encog.util.text.Base64
-
Specify encoding in first bit.
- encode(ByteBuffer, ByteBuffer) - Static method in class org.encog.util.text.Base64
-
Performs Base64 encoding on the raw
ByteBuffer,
writing it to the encoded
ByteBuffer.
- encode(ByteBuffer, CharBuffer) - Static method in class org.encog.util.text.Base64
-
Performs Base64 encoding on the raw
ByteBuffer,
writing it to the encoded
CharBuffer.
- encodeBytes(byte[]) - Static method in class org.encog.util.text.Base64
-
Encodes a byte array into Base64 notation.
- encodeBytes(byte[], int) - Static method in class org.encog.util.text.Base64
-
Encodes a byte array into Base64 notation.
- encodeBytes(byte[], int, int) - Static method in class org.encog.util.text.Base64
-
Encodes a byte array into Base64 notation.
- encodeBytes(byte[], int, int, int) - Static method in class org.encog.util.text.Base64
-
Encodes a byte array into Base64 notation.
- encodeBytesToBytes(byte[]) - Static method in class org.encog.util.text.Base64
-
- encodeBytesToBytes(byte[], int, int, int) - Static method in class org.encog.util.text.Base64
-
- encodedArrayLength() - Method in interface org.encog.ml.MLEncodable
-
- encodedArrayLength() - Method in class org.encog.neural.freeform.FreeformNetwork
- encodedArrayLength() - Method in class org.encog.neural.networks.BasicNetwork
- encodedArrayLength() - Method in class org.encog.neural.rbf.RBFNetwork
- encodeEquilateral(int) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Perform an equilateral encode.
- encodeFileToFile(String, String) - Static method in class org.encog.util.text.Base64
-
Reads infile and encodes it to outfile.
- encodeFromFile(String) - Static method in class org.encog.util.text.Base64
-
Convenience method for reading a binary file
and base64-encoding it.
- encodeHeaders() - Method in class org.encog.util.arrayutil.NormalizedField
-
Encode the headers used by this field.
- encodeNetwork() - Method in class org.encog.neural.flat.FlatNetwork
-
Encode the neural network to an array of doubles.
- encodeObject(Serializable) - Static method in class org.encog.util.text.Base64
-
Serializes an object and returns the Base64-encoded
version of that serialized object.
- encodeObject(Serializable, int) - Static method in class org.encog.util.text.Base64
-
Serializes an object and returns the Base64-encoded
version of that serialized object.
- EncoderTrainingFactory - Class in org.encog.util.benchmark
-
This benchmark implements a Fahlman Encoder.
- EncoderTrainingFactory() - Constructor for class org.encog.util.benchmark.EncoderTrainingFactory
-
- encodeSingleField(int) - Method in class org.encog.util.arrayutil.NormalizedField
-
Encode a single field.
- EncodeSVMProblem - Class in org.encog.ml.svm.training
-
Encode an Encog dataset as a SVM problem.
- encodeToArray(double[]) - Method in interface org.encog.ml.MLEncodable
-
Encode the object to the specified array.
- encodeToArray(double[]) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Encode the object to the specified array.
- encodeToArray(double[]) - Method in class org.encog.neural.networks.BasicNetwork
-
Encode the object to the specified array.
- encodeToArray(double[]) - Method in class org.encog.neural.rbf.RBFNetwork
-
Encode the object to the specified array.
- encodeToFile(byte[], String) - Static method in class org.encog.util.text.Base64
-
Convenience method for encoding data to a file.
- Encog - Class in org.encog
-
Main Encog class, does little more than provide version information.
- ENCOG_FILE_VERSION - Static variable in class org.encog.Encog
-
The encog file version.
- ENCOG_VERSION - Static variable in class org.encog.Encog
-
The version of the Encog JAR we are working with.
- EncogAnalyst - Class in org.encog.app.analyst
-
The Encog Analyst runs Encog Analyst Script files (EGA) to perform many
common machine learning tasks.
- EncogAnalyst() - Constructor for class org.encog.app.analyst.EncogAnalyst
-
Construct the Encog analyst.
- EncogArgType - Enum in org.encog.app.generate.program
-
The type of argument.
- EncogBenchmark - Class in org.encog.util.benchmark
-
Benchmark Encog with several network types.
- EncogBenchmark(StatusReportable) - Constructor for class org.encog.util.benchmark.EncogBenchmark
-
Construct a benchmark object.
- EncogCodeGeneration - Class in org.encog.app.generate
-
Perform Encog code generation.
- EncogCodeGeneration(TargetLanguage) - Constructor for class org.encog.app.generate.EncogCodeGeneration
-
Construct the generation object.
- EncogDirectoryPersistence - Class in org.encog.persist
-
Handles Encog persistence for a directory.
- EncogDirectoryPersistence(File) - Constructor for class org.encog.persist.EncogDirectoryPersistence
-
Construct the object.
- EncogEGBFile - Class in org.encog.ml.data.buffer
-
Used to access an Encog Binary Training file (*.EGB).
- EncogEGBFile(File) - Constructor for class org.encog.ml.data.buffer.EncogEGBFile
-
Construct an EGB file.
- EncogError - Exception in org.encog
-
General error class for Encog.
- EncogError(String) - Constructor for exception org.encog.EncogError
-
Construct a message exception.
- EncogError(Throwable) - Constructor for exception org.encog.EncogError
-
Construct an exception that holds another exception.
- EncogError(String, Throwable) - Constructor for exception org.encog.EncogError
-
Construct an exception that holds another exception.
- EncogFileSection - Class in org.encog.persist
-
This class is used internally to parse Encog files.
- EncogFileSection(String, String) - Constructor for class org.encog.persist.EncogFileSection
-
Construct the object.
- EncogFormatter - Class in org.encog.util.logging
-
A simple formatter for logging.
- EncogFormatter() - Constructor for class org.encog.util.logging.EncogFormatter
-
- EncogFunction - Interface in org.encog.mathutil
-
A generic single or multivariate function.
- EncogGenProgram - Class in org.encog.app.generate.program
-
Holds a generated Encog program.
- EncogGenProgram() - Constructor for class org.encog.app.generate.program.EncogGenProgram
-
Construct the program.
- EncogLogging - Class in org.encog.util.logging
-
This class provides logging for Encog.
- EncogLogging() - Constructor for class org.encog.util.logging.EncogLogging
-
- EncogMath - Class in org.encog.mathutil
-
Several useful math functions for Encog.
- EncogMathError - Exception in org.encog.mathutil
-
Thrown when a math error happens.
- EncogMathError(String) - Constructor for exception org.encog.mathutil.EncogMathError
-
Construct a message exception.
- EncogMathError(String, Throwable) - Constructor for exception org.encog.mathutil.EncogMathError
-
Construct an exception that holds another exception.
- EncogMathError(Throwable) - Constructor for exception org.encog.mathutil.EncogMathError
-
Construct an exception that holds another exception.
- EncogModel - Class in org.encog.ml.model
-
Encog model is designed to allow you to easily swap between different model
types and automatically normalize data.
- EncogModel(VersatileMLDataSet) - Constructor for class org.encog.ml.model.EncogModel
-
Construct a model for the specified dataset.
- EncogOpcodeRegistry - Enum in org.encog.ml.prg.extension
-
Holds all known EPL opcodes.
- EncogPersistor - Interface in org.encog.persist
-
This interface defines an Encog Persistor.
- EncogPlatformSpecific - Class in org.encog.platformspecific.j2se
-
- EncogPlatformSpecific() - Constructor for class org.encog.platformspecific.j2se.EncogPlatformSpecific
-
- EncogPluginBase - Interface in org.encog.plugin
-
The base plugin for Encog.
- EncogPluginLogging1 - Interface in org.encog.plugin
-
A plugin that supports logging.
- EncogPluginService1 - Interface in org.encog.plugin
-
A service plugin provides services, such as the creation of activation
functions, machine learning methods and training methods.
- EncogProgram - Class in org.encog.ml.prg
-
Holds an Encog Programming Language (EPL) program.
- EncogProgram() - Constructor for class org.encog.ml.prg.EncogProgram
-
Construct the Encog program and create a default context and variable
holder.
- EncogProgram(EncogProgramContext) - Constructor for class org.encog.ml.prg.EncogProgram
-
Construct the Encog program with the specified context, but create a new
variable holder.
- EncogProgram(EncogProgramContext, EncogProgramVariables) - Constructor for class org.encog.ml.prg.EncogProgram
-
Construct an Encog program using the specified context and variable
holder.
- EncogProgram(String) - Constructor for class org.encog.ml.prg.EncogProgram
-
Construct an Encog program using the specified expression, but create an
empty context and variable holder.
- EncogProgramArg - Class in org.encog.app.generate.program
-
A function argument for Encog created code.
- EncogProgramArg(double) - Constructor for class org.encog.app.generate.program.EncogProgramArg
-
Construct the argument.
- EncogProgramArg(EncogArgType, Object) - Constructor for class org.encog.app.generate.program.EncogProgramArg
-
Construct the argument.
- EncogProgramArg(int) - Constructor for class org.encog.app.generate.program.EncogProgramArg
-
Construct a floating point arguement from an integer.
- EncogProgramArg(Object) - Constructor for class org.encog.app.generate.program.EncogProgramArg
-
Construct using an object.
- EncogProgramArg(String) - Constructor for class org.encog.app.generate.program.EncogProgramArg
-
Construct a string argument.
- EncogProgramContext - Class in org.encog.ml.prg
-
Every EncogProgram must belong to a context.
- EncogProgramContext() - Constructor for class org.encog.ml.prg.EncogProgramContext
-
Construct the context with an English number format and an empty function
factory.
- EncogProgramContext(CSVFormat) - Constructor for class org.encog.ml.prg.EncogProgramContext
-
Construct a context with the specified number format and an empty
function factory.
- EncogProgramContext(CSVFormat, FunctionFactory) - Constructor for class org.encog.ml.prg.EncogProgramContext
-
Construct the context with the specified format and function factory.
- EncogProgramNode - Class in org.encog.app.generate.program
-
A node that holds a program.
- EncogProgramNode(EncogGenProgram, EncogTreeNode, NodeType, String) - Constructor for class org.encog.app.generate.program.EncogProgramNode
-
Construct the program node.
- EncogProgramVariables - Class in org.encog.ml.prg
-
This class stores the actual variable values for an Encog Program.
- EncogProgramVariables() - Constructor for class org.encog.ml.prg.EncogProgramVariables
-
- EncogReadHelper - Class in org.encog.persist
-
Used to read an Encog EG/EGA file.
- EncogReadHelper(InputStream) - Constructor for class org.encog.persist.EncogReadHelper
-
Construct the object.
- EncogShutdownTask - Interface in org.encog
-
- EncogTreeNode - Class in org.encog.app.generate.program
-
A tree node that represents code to be generated.
- EncogTreeNode(EncogGenProgram, EncogTreeNode) - Constructor for class org.encog.app.generate.program.EncogTreeNode
-
Construct a tree node.
- EncogUtility - Class in org.encog.util.simple
-
General utility class for Encog.
- EncogValidate - Class in org.encog.util
-
Used to validate if training is valid.
- EncogWriteHelper - Class in org.encog.persist
-
Used to write an Encog EG/EGA file.
- EncogWriteHelper(OutputStream) - Constructor for class org.encog.persist.EncogWriteHelper
-
Construct the object.
- endBar() - Method in class org.encog.app.quant.ninja.NinjaStreamWriter
-
End the current bar.
- endBody() - Method in class org.encog.util.HTMLReport
-
- endDocument() - Method in class org.encog.ml.bayesian.bif.BIFHandler
- endDocument() - Method in class org.encog.parse.tags.write.WriteTags
-
End the document.
- endElement(String, String, String) - Method in class org.encog.ml.bayesian.bif.BIFHandler
- endHTML() - Method in class org.encog.util.HTMLReport
-
- EndIterationsStrategy - Class in org.encog.ml.train.strategy.end
-
- EndIterationsStrategy(int) - Constructor for class org.encog.ml.train.strategy.end.EndIterationsStrategy
-
- endList() - Method in class org.encog.util.HTMLReport
-
- endLoad() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
This method should be called once all the data has been loaded.
- EndMaxErrorStrategy - Class in org.encog.ml.train.strategy.end
-
- EndMaxErrorStrategy(double) - Constructor for class org.encog.ml.train.strategy.end.EndMaxErrorStrategy
-
- EndMinutesStrategy - Class in org.encog.ml.train.strategy.end
-
- EndMinutesStrategy(int) - Constructor for class org.encog.ml.train.strategy.end.EndMinutesStrategy
-
- endPara() - Method in class org.encog.util.HTMLReport
-
- endRow() - Method in class org.encog.util.HTMLReport
-
- endTable() - Method in class org.encog.util.HTMLReport
-
- endTableInCell() - Method in class org.encog.util.HTMLReport
-
- endTag() - Method in class org.encog.parse.tags.write.WriteTags
-
End the current tag.
- endTag(String) - Method in class org.encog.parse.tags.write.WriteTags
-
End a tag, require that we are ending the specified tag.
- EndTrainingStrategy - Interface in org.encog.ml.train.strategy.end
-
- enforceLimit() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
Enforce that all connections are above the connection limit.
- EngineArray - Class in org.encog.util
-
Some array functions used by Encog.
- EngineConcurrency - Class in org.encog.util.concurrency
-
This class abstracts thread pools, and potentially grids and other types of
concurrency.
- EngineConcurrency() - Constructor for class org.encog.util.concurrency.EngineConcurrency
-
Construct a concurrency object.
- EngineTask - Interface in org.encog.util.concurrency
-
An individual task that can be submitted to the EncogCurrency utility.
- ENGLISH - Static variable in class org.encog.util.csv.CSVFormat
-
Decimal point is typically used in English speaking counties.
- EnglishTimeUnitNames - Class in org.encog.util.time
-
Class used to get the English names for TimeUnits.
- EnglishTimeUnitNames() - Constructor for class org.encog.util.time.EnglishTimeUnitNames
-
- Ensemble - Class in org.encog.ensemble
-
- Ensemble() - Constructor for class org.encog.ensemble.Ensemble
-
- Ensemble.NotPossibleInThisMethod - Exception in org.encog.ensemble
-
- Ensemble.NotPossibleInThisMethod() - Constructor for exception org.encog.ensemble.Ensemble.NotPossibleInThisMethod
-
- EnsembleAggregator - Interface in org.encog.ensemble
-
- EnsembleDataSet - Class in org.encog.ensemble.data
-
- EnsembleDataSet(int, int) - Constructor for class org.encog.ensemble.data.EnsembleDataSet
-
- EnsembleDataSet(MLDataSet) - Constructor for class org.encog.ensemble.data.EnsembleDataSet
-
- EnsembleDataSetFactory - Class in org.encog.ensemble.data.factories
-
- EnsembleDataSetFactory(int) - Constructor for class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- EnsembleML - Interface in org.encog.ensemble
-
- EnsembleMLMethodFactory - Interface in org.encog.ensemble
-
- EnsembleTrainFactory - Interface in org.encog.ensemble
-
- EnsembleTypes - Class in org.encog.ensemble
-
- EnsembleTypes() - Constructor for class org.encog.ensemble.EnsembleTypes
-
- EnsembleTypes.ProblemType - Enum in org.encog.ensemble
-
- EnumerationQuery - Class in org.encog.ml.bayesian.query.enumerate
-
An enumeration query allows probabilistic queries on a Bayesian network.
- EnumerationQuery(BayesianNetwork) - Constructor for class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
-
Construct the enumeration query.
- EnumerationQuery() - Constructor for class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
-
Default constructor.
- eol() - Method in class org.encog.util.SimpleParser
-
- EPLFactory - Class in org.encog.ml.factory.method
-
- EPLFactory() - Constructor for class org.encog.ml.factory.method.EPLFactory
-
- EPLGAFactory - Class in org.encog.ml.factory.train
-
- EPLGAFactory() - Constructor for class org.encog.ml.factory.train.EPLGAFactory
-
- eps - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- EPSILON_SVR - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- equ(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform an equal on two expressions.
- equals(Matrix, int) - Method in class org.encog.mathutil.matrices.Matrix
-
Compare to matrixes with the specified level of precision.
- equals(Object) - Method in class org.encog.mathutil.matrices.Matrix
-
Check to see if this matrix equals another, using default precision.
- equals(Object) - Method in class org.encog.ml.data.market.TickerSymbol
- equals(Object) - Method in class org.encog.neural.neat.NEATLink
- equals(Object) - Method in class org.encog.neural.networks.BasicNetwork
-
Compare the two neural networks.
- equals(BasicNetwork, int) - Method in class org.encog.neural.networks.BasicNetwork
-
Determine if this neural network is equal to another.
- equals(BasicNetwork, BasicNetwork) - Static method in class org.encog.neural.networks.structure.NetworkCODEC
-
Determine if the two neural networks are equal.
- equals(BasicNetwork, BasicNetwork, int) - Static method in class org.encog.neural.networks.structure.NetworkCODEC
-
Determine if the two neural networks are equal.
- Equilateral - Class in org.encog.mathutil
-
Used to produce an array of activations to classify data into groups.
- Equilateral(int, double, double) - Constructor for class org.encog.mathutil.Equilateral
-
Construct an equilateral matrix.
- ERROR - Static variable in class org.encog.persist.PersistConst
-
Error.
- ERROR_ADD - Static variable in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Error message for ADD.
- ERROR_REMOVE - Static variable in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Error message for REMOVE.
- ErrorCalculation - Class in org.encog.mathutil.error
-
Calculate the error of a neural network.
- ErrorCalculation() - Constructor for class org.encog.mathutil.error.ErrorCalculation
-
- ErrorCalculationMode - Enum in org.encog.mathutil.error
-
Selects the error calculation mode for Encog.
- ErrorFunction - Interface in org.encog.neural.error
-
An error function.
- establishEquilibrium() - Method in class org.encog.neural.thermal.BoltzmannMachine
-
Run the network until thermal equilibrium is established.
- estimateCost(BasicNode, SearchGoal) - Method in interface org.encog.ml.graph.search.CostEstimator
-
- estimateCost(BasicNode, SearchGoal) - Method in class org.encog.ml.graph.search.EuclideanCostEstimator
-
- estimateGamma(double[][][], ForwardBackwardCalculator) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- estimateGamma(double[][][], ForwardBackwardCalculator) - Method in class org.encog.ml.hmm.train.bw.TrainBaumWelch
-
- estimateXi(MLDataSet, ForwardBackwardCalculator, HiddenMarkovModel) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- estimateXi(MLDataSet, ForwardBackwardCalculator, HiddenMarkovModel) - Method in class org.encog.ml.hmm.train.bw.TrainBaumWelch
-
- estimateXi(MLDataSet, ForwardBackwardCalculator, HiddenMarkovModel) - Method in class org.encog.ml.hmm.train.bw.TrainBaumWelchScaled
-
- EstimatorNone - Class in org.encog.ml.bayesian.training.estimator
-
A simple estimator that does nothing.
- EstimatorNone() - Constructor for class org.encog.ml.bayesian.training.estimator.EstimatorNone
-
- EuclideanCostEstimator - Class in org.encog.ml.graph.search
-
- EuclideanCostEstimator() - Constructor for class org.encog.ml.graph.search.EuclideanCostEstimator
-
- euclideanDistance(GridState, GridState) - Static method in class org.encog.ml.world.grid.GridWorld
-
- euclideanDistance(double[], double[]) - Static method in class org.encog.util.EngineArray
-
- EuclideanNode - Class in org.encog.ml.graph
-
- EuclideanNode(String, double[]) - Constructor for class org.encog.ml.graph.EuclideanNode
-
- EuclideanNode(String, double, double) - Constructor for class org.encog.ml.graph.EuclideanNode
-
- EULERS_NUMBER - Static variable in class org.encog.mathutil.MathConst
-
Euler's number.
- evaluate(ArrayList<MLData>) - Method in class org.encog.ensemble.aggregator.Averaging
-
- evaluate(ArrayList<MLData>, double, double, double) - Method in class org.encog.ensemble.aggregator.MajorityVoting
-
- evaluate(ArrayList<MLData>) - Method in class org.encog.ensemble.aggregator.MajorityVoting
-
- evaluate(ArrayList<MLData>) - Method in class org.encog.ensemble.aggregator.MetaClassifier
-
- evaluate(ArrayList<MLData>) - Method in interface org.encog.ensemble.EnsembleAggregator
-
- evaluate() - Method in class org.encog.ml.prg.EncogProgram
-
Execute the program and return the result.
- evaluate(ProgramNode) - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
Evaluate the specified actual program node, using this opcode template.
- evaluate() - Method in class org.encog.ml.prg.ProgramNode
-
- Evaluate - Class in org.encog.util.benchmark
-
Used to evaluate the training time for a network.
- Evaluate() - Constructor for class org.encog.util.benchmark.Evaluate
-
- evaluate(MLRegression, MLDataSet) - Static method in class org.encog.util.simple.EncogUtility
-
Evaluate the network and display (to the console) the output for every
value in the training set.
- EvaluateExpr - Class in org.encog.ml.prg.expvalue
-
Simple utility class that performs some basic operations on ExpressionValue
objects.
- evaluateTrain(int, int, int, int) - Static method in class org.encog.util.benchmark.Evaluate
-
- evaluateTrain(BasicNetwork, MLDataSet) - Static method in class org.encog.util.benchmark.Evaluate
-
Evaluate how long it takes to calculate the error for the network.
- eventExists(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Return true if the specified event exists.
- EventState - Class in org.encog.ml.bayesian.query.sample
-
Holds the state of an event during a query.
- EventState(BayesianEvent) - Constructor for class org.encog.ml.bayesian.query.sample.EventState
-
Construct an event state for the specified event.
- EventType - Enum in org.encog.ml.bayesian
-
The type of event for a Bayesian Network.
- EvolutionaryAlgorithm - Interface in org.encog.ml.ea.train
-
This interface defines the basic functionality of an Evolutionary Algorithm.
- EvolutionaryOperator - Interface in org.encog.ml.ea.opp
-
An evolutionary operator is used to create new offspring genomes based on
parent genomes.
- ExcelCODEC - Class in org.encog.ml.data.buffer.codec
-
A CODEC that can read/write Microsoft Excel (*.XLSX) files.
- ExcelCODEC(File) - Constructor for class org.encog.ml.data.buffer.codec.ExcelCODEC
-
Constructor to create Excel from binary.
- ExcelCODEC(File, int, int) - Constructor for class org.encog.ml.data.buffer.codec.ExcelCODEC
-
Create a CODEC to load data from Excel to binary.
- exclude(int, String) - Method in class org.encog.app.analyst.csv.filter.FilterCSV
-
Exclude rows where the specified field has the specified value.
- ExcludedField - Class in org.encog.app.analyst.csv.filter
-
Used internally to track excluded fields from the FilterCSV.
- ExcludedField(int, String) - Constructor for class org.encog.app.analyst.csv.filter.ExcludedField
-
Construct the object.
- execute() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
Execute the query.
- execute() - Method in class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
-
Execute the query.
- execute() - Method in class org.encog.ml.bayesian.query.sample.SamplingQuery
-
Execute the query.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.Cmd
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdBalance
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdCluster
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdCode
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdCreate
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdEvaluate
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdEvaluateRaw
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdGenerate
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdNormalize
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdProcess
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdRandomize
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdReset
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdSegregate
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdSet
-
Execute this command.
- executeCommand(String) - Method in class org.encog.app.analyst.commands.CmdTrain
-
Execute this command.
- executeTask(AnalystTask) - Method in class org.encog.app.analyst.EncogAnalyst
-
Execute a task.
- executeTask(String) - Method in class org.encog.app.analyst.EncogAnalyst
-
Execute a task.
- exp(double) - Static method in class org.encog.mathutil.BoundMath
-
Calculate the exp.
- exp() - Method in class org.encog.mathutil.ComplexNumber
-
Complex exponential (doesn't change this Complex number).
- expectInputHeaders(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
Determine if input headers are expected.
- explainErrorMSE(MLRegression, MatrixMLDataSet) - Static method in class org.encog.util.simple.EncogUtility
-
- explainErrorRMS(MLRegression, MatrixMLDataSet) - Static method in class org.encog.util.simple.EncogUtility
-
- ExpressionNodeType - Enum in org.encog.parse.expression
-
- ExpressionValue - Class in org.encog.ml.prg.expvalue
-
An EncogProgram expression value.
- ExpressionValue(boolean) - Constructor for class org.encog.ml.prg.expvalue.ExpressionValue
-
Construct a boolean expression.
- ExpressionValue(double) - Constructor for class org.encog.ml.prg.expvalue.ExpressionValue
-
Construct a boolean expression.
- ExpressionValue(ExpressionValue) - Constructor for class org.encog.ml.prg.expvalue.ExpressionValue
-
Construct a expression based on an expression.
- ExpressionValue(int, long) - Constructor for class org.encog.ml.prg.expvalue.ExpressionValue
-
Construct an enum expression.
- ExpressionValue(long) - Constructor for class org.encog.ml.prg.expvalue.ExpressionValue
-
Construct an integer expression.
- ExpressionValue(String) - Constructor for class org.encog.ml.prg.expvalue.ExpressionValue
-
Construct a string expression.
- ExpressionValue(ValueType) - Constructor for class org.encog.ml.prg.expvalue.ExpressionValue
-
Construct a value of the specified type.
- EXTENSION_ABS - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric absolute value function.
- EXTENSION_ACOS - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric acos function.
- EXTENSION_ADD - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard binary add operator.
- EXTENSION_AND - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary and operator.
- EXTENSION_ASIN - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric asin function.
- EXTENSION_ATAN - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric atan function.
- EXTENSION_ATAN2 - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric atan2 function.
- EXTENSION_CBOOL - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard string cbool function.
- EXTENSION_CEIL - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric ceil function.
- EXTENSION_CFLOAT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard string cfloat function.
- EXTENSION_CINT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard string cint function.
- EXTENSION_CLAMP - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard string clamp function.
- EXTENSION_CONST_SUPPORT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Numeric const.
- EXTENSION_COS - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric cos function.
- EXTENSION_COSH - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric cosh function.
- EXTENSION_CSTR - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard string cstr function.
- EXTENSION_DATA_NAME - Static variable in class org.encog.app.analyst.csv.process.ProcessExtension
-
- EXTENSION_DIV - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard binary div operator.
- EXTENSION_EQUAL - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary equal operator.
- EXTENSION_EXP - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric exp function.
- EXTENSION_FLOOR - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric floor function.
- EXTENSION_FORMAT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Numeric formatting function.
- EXTENSION_GT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary greater than operator.
- EXTENSION_GTE - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary greater than operator.
- EXTENSION_IFF - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard string iff function.
- EXTENSION_LEFT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
String left function.
- EXTENSION_LENGTH - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard string length function.
- EXTENSION_LOG - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric log function.
- EXTENSION_LOG10 - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric log10 function.
- EXTENSION_LT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary less than operator.
- EXTENSION_LTE - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary less than operator.
- EXTENSION_MAX - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric max function.
- EXTENSION_MIN - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric max function.
- EXTENSION_MUL - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard binary multiply operator.
- EXTENSION_NEG - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard unary minus operator.
- EXTENSION_NOT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary and operator.
- EXTENSION_NOT_EQUAL - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean not equal operator.
- EXTENSION_OR - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard boolean binary or operator.
- EXTENSION_PDIV - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard binary protected div operator.
- EXTENSION_POWER - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard binary power operator.
- EXTENSION_POWFN - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric pow function.
- EXTENSION_RANDOM - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric random function.
- EXTENSION_RIGHT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
String right function.
- EXTENSION_ROUND - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric log10 function.
- EXTENSION_SIN - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric sin function.
- EXTENSION_SINH - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric sinh function.
- EXTENSION_SQRT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric sqrt function.
- EXTENSION_SUB - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard binary sub operator.
- EXTENSION_TAN - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric tan function.
- EXTENSION_TANH - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric tanh function.
- EXTENSION_TODEG - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric toDegrees function.
- EXTENSION_TORAD - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Standard numeric toRadians function.
- EXTENSION_VAR_SUPPORT - Static variable in class org.encog.ml.prg.extension.StandardExtensions
-
Variable support.
- external2Binary(File) - Method in class org.encog.ml.data.buffer.BinaryDataLoader
-
Convert an external file format, such as CSV, to the Encog binary
training format.
- external2Memory() - Method in class org.encog.ml.data.buffer.MemoryDataLoader
-
Convert an external file format, such as CSV, to an Encog memory training
set.
- extract(String, String, String, int) - Static method in class org.encog.bot.BotUtil
-
This method is very useful for grabbing information from a HTML page.
- extractFields(EncogAnalyst, CSVHeaders, ReadCSV, int, boolean) - Static method in class org.encog.app.analyst.csv.normalize.AnalystNormalizeCSV
-
Extract fields from a file into a numeric array for machine learning.
- extractFromIndex(String, String, String, int, int) - Static method in class org.encog.bot.BotUtil
-
This method is very useful for grabbing information from a HTML page.
- factor() - Method in class org.encog.ca.universe.basic.BasicCellFactory
-
- factor() - Method in interface org.encog.ca.universe.UniverseCellFactory
-
- factor() - Method in class org.encog.mathutil.randomize.factory.BasicRandomFactory
-
- factor() - Method in interface org.encog.mathutil.randomize.factory.RandomFactory
-
- factor() - Method in interface org.encog.ml.ea.genome.GenomeFactory
-
- factor(Genome) - Method in interface org.encog.ml.ea.genome.GenomeFactory
-
Create a clone of the other genome.
- factor() - Method in class org.encog.ml.genetic.genome.DoubleArrayGenomeFactory
- factor(Genome) - Method in class org.encog.ml.genetic.genome.DoubleArrayGenomeFactory
-
Create a clone of the other genome.
- factor() - Method in class org.encog.ml.genetic.genome.IntegerArrayGenomeFactory
- factor(Genome) - Method in class org.encog.ml.genetic.genome.IntegerArrayGenomeFactory
-
Create a clone of the other genome.
- factor() - Method in class org.encog.ml.genetic.MLMethodGenomeFactory
- factor(Genome) - Method in class org.encog.ml.genetic.MLMethodGenomeFactory
-
Create a clone of the other genome.
- factor() - Method in interface org.encog.ml.MethodFactory
-
- factor() - Method in class org.encog.ml.prg.train.PrgGenomeFactory
- factor(Genome) - Method in class org.encog.ml.prg.train.PrgGenomeFactory
-
Create a clone of the other genome.
- factor(ActivationFunction) - Method in class org.encog.neural.freeform.basic.BasicActivationSummationFactory
-
Create a new input summation.
- factor(FreeformNeuron, FreeformNeuron) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnectionFactory
-
Create a connection.
- factor() - Method in class org.encog.neural.freeform.basic.BasicFreeformLayerFactory
-
Create a layer.
- factor(FreeformNeuron, FreeformNeuron) - Method in interface org.encog.neural.freeform.factory.FreeformConnectionFactory
-
Create a connection.
- factor() - Method in interface org.encog.neural.freeform.factory.FreeformLayerFactory
-
Create a layer.
- factor(ActivationFunction) - Method in interface org.encog.neural.freeform.factory.InputSummationFactory
-
Create a new input summation.
- factor() - Method in class org.encog.neural.hyperneat.FactorHyperNEATGenome
- factor(Genome) - Method in class org.encog.neural.hyperneat.FactorHyperNEATGenome
-
Create a clone of the other genome.
- factor(List<NEATNeuronGene>, List<NEATLinkGene>, int, int) - Method in class org.encog.neural.hyperneat.FactorHyperNEATGenome
-
Create a NEAT genome from a list of links and neurons.
- factor(Random, NEATPopulation, int, int, double) - Method in class org.encog.neural.hyperneat.FactorHyperNEATGenome
-
Create a new random NEAT genome.
- factor() - Method in class org.encog.neural.neat.FactorNEATGenome
- factor(Genome) - Method in class org.encog.neural.neat.FactorNEATGenome
-
Create a clone of the other genome.
- factor(List<NEATNeuronGene>, List<NEATLinkGene>, int, int) - Method in class org.encog.neural.neat.FactorNEATGenome
-
Create a NEAT genome from a list of links and neurons.
- factor(Random, NEATPopulation, int, int, double) - Method in class org.encog.neural.neat.FactorNEATGenome
-
Create a new random NEAT genome.
- factor(List<NEATNeuronGene>, List<NEATLinkGene>, int, int) - Method in interface org.encog.neural.neat.NEATGenomeFactory
-
Create a NEAT genome from a list of links and neurons.
- factor(Random, NEATPopulation, int, int, double) - Method in interface org.encog.neural.neat.NEATGenomeFactory
-
Create a new random NEAT genome.
- factorContext(FreeformNeuron) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuronFactory
-
Create a context neuron.
- factorContext(FreeformNeuron) - Method in interface org.encog.neural.freeform.factory.FreeformNeuronFactory
-
Create a context neuron.
- factorFactory() - Method in class org.encog.mathutil.randomize.factory.BasicRandomFactory
-
- factorFactory() - Method in interface org.encog.mathutil.randomize.factory.RandomFactory
-
- FactorHyperNEATGenome - Class in org.encog.neural.hyperneat
-
Create a Genome for use with HyperNEAT.
- FactorHyperNEATGenome() - Constructor for class org.encog.neural.hyperneat.FactorHyperNEATGenome
-
- factorial(int) - Static method in class org.encog.mathutil.EncogMath
-
Calculate x!.
- FactorNEATGenome - Class in org.encog.neural.neat
-
This factory is used to create NEATGenomes.
- FactorNEATGenome() - Constructor for class org.encog.neural.neat.FactorNEATGenome
-
- factorProgramNode(ProgramExtensionTemplate, EncogProgram, ProgramNode[]) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Factor a new program node, based in a template object.
- factorProgramNode(String, EncogProgram, ProgramNode[]) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Factor a new program node, based on an opcode name and arguments.
- factorRegular(InputSummation) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuronFactory
-
Create a regular neuron.
- factorRegular(InputSummation) - Method in interface org.encog.neural.freeform.factory.FreeformNeuronFactory
-
Create a regular neuron.
- factorSandwichSubstrate(int, int) - Static method in class org.encog.neural.hyperneat.substrate.SubstrateFactory
-
Create a sandwich substrate.
- FanInRandomizer - Class in org.encog.mathutil.randomize
-
A randomizer that attempts to create starting weight values that are
conducive to propagation training.
- FanInRandomizer() - Constructor for class org.encog.mathutil.randomize.FanInRandomizer
-
Create a fan-in randomizer with default values.
- FanInRandomizer(double, boolean) - Constructor for class org.encog.mathutil.randomize.FanInRandomizer
-
Construct a fan-in randomizer along the specified boundary.
- FanInRandomizer(double, double, boolean) - Constructor for class org.encog.mathutil.randomize.FanInRandomizer
-
Construct a fan-in randomizer.
- FeedforwardConfig - Class in org.encog.ml.model.config
-
Config class for EncogModel to use a feedforward neural network.
- FeedforwardConfig() - Constructor for class org.encog.ml.model.config.FeedforwardConfig
-
- FeedforwardFactory - Class in org.encog.ml.factory.method
-
A factor to create feedforward networks.
- FeedforwardFactory() - Constructor for class org.encog.ml.factory.method.FeedforwardFactory
-
- FeedForwardPattern - Class in org.encog.neural.pattern
-
Used to create feedforward neural networks.
- FeedForwardPattern() - Constructor for class org.encog.neural.pattern.FeedForwardPattern
-
- FieldDirection - Enum in org.encog.app.analyst.util
-
- FieldPreprocess - Class in org.encog.app.analyst.script.preprocess
-
- FieldPreprocess(PreprocessAction, String, String) - Constructor for class org.encog.app.analyst.script.preprocess.FieldPreprocess
-
- FILE_BALANCE - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The balanced file.
- FILE_CLUSTER - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The clustered file.
- FILE_CODE - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The generated code file.
- FILE_EVAL - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The evaluation file.
- FILE_EVAL_NORM - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The eval file normalization file.
- FILE_ML - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The machine learning file.
- FILE_NORMALIZE - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The normalized file.
- FILE_OUTPUT - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The output file.
- FILE_PRE - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The processed data.
- FILE_RANDOM - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The randomized file.
- FILE_RAW - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The raw file.
- FILE_TRAIN - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The training file.
- FILE_TRAINSET - Static variable in class org.encog.app.analyst.wizard.AnalystWizard
-
The training set.
- FileData - Class in org.encog.app.analyst.csv.basic
-
A column that is based off of a column in a CSV file.
- FileData(String, int, boolean, boolean) - Constructor for class org.encog.app.analyst.csv.basic.FileData
-
Construct the object.
- FileSection - Enum in org.encog.ml.bayesian.bif
-
The section of the BIF file that we are currently in.
- FileUtil - Class in org.encog.util.file
-
- FileUtil() - Constructor for class org.encog.util.file.FileUtil
-
- fill(double[], double) - Static method in class org.encog.util.EngineArray
-
Fill a double array.
- fill(float[], float) - Static method in class org.encog.util.EngineArray
-
Fill a float array.
- fill(double[][], int) - Static method in class org.encog.util.EngineArray
-
- fill(boolean[], boolean) - Static method in class org.encog.util.EngineArray
-
- fill(int[], int) - Static method in class org.encog.util.EngineArray
-
- FilterCSV - Class in org.encog.app.analyst.csv.filter
-
This class can be used to remove certain rows from a CSV.
- FilterCSV() - Constructor for class org.encog.app.analyst.csv.filter.FilterCSV
-
- finalizeField() - Method in class org.encog.app.analyst.analyze.AnalyzedField
-
Finalize the field, and create a DataField.
- finalizeLimit() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
Parse/finalize the limit value for connections.
- finalizeStructure() - Method in class org.encog.ml.bayesian.BayesianEvent
-
Finalize the structure.
- finalizeStructure() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Finalize the structure of this Bayesian network.
- finalizeStructure() - Method in class org.encog.ml.bayesian.query.BasicQuery
-
- finalizeStructure() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- finalizeStructure() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
Build the synapse and layer structure.
- finalizeStructure() - Method in class org.encog.util.obj.ChooseObject
-
Finalize the structure and set the probabilities.
- finalizeTraining() - Method in class org.encog.ml.fitting.gaussian.GaussianFitting
-
- find(String) - Method in class org.encog.app.analyst.util.CSVHeaders
-
Find the specified column.
- find(Class<?>, int) - Method in class org.encog.bot.browse.WebPage
-
Find the specified DocumentRange subclass in the contents list.
- findAllOpcodes() - Method in enum org.encog.ml.prg.extension.EncogOpcodeRegistry
-
- findAnalystField(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
- findBestRange(double, double, int, boolean, double, CalculationCriteria) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
Find the best common gamma.
- findBestSpecies() - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
Find the best species.
- findBounds() - Method in interface org.encog.util.downsample.Downsample
-
Find the bounds around the image to exclude whitespace.
- findBounds() - Method in class org.encog.util.downsample.RGBDownsample
-
This method is called to automatically crop the image so that whitespace
is removed.
- findClass(int) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- findClosestStateTo(List<GridState>, GridState) - Method in class org.encog.ml.world.grid.GridWorld
-
- findClosestStateToGoal(List<GridState>) - Method in class org.encog.ml.world.grid.GridWorld
-
- findDataField(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
Find the specified data field.
- findDataFieldIndex(DataField) - Method in class org.encog.app.analyst.script.AnalystScript
-
Find the specified data field and return its index.
- findEndTag(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage
-
Find the end tag that lines up to the beginning tag.
- findEntry(String) - Method in class org.encog.app.analyst.script.prop.PropertyConstraints
-
Find an entry based on a string.
- findField(Class<?>, String) - Static method in class org.encog.util.obj.ReflectionUtil
-
Find the specified field, look also in superclasses.
- findFunction(String) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Find a function with the specified name.
- findIndex(int) - Method in class org.encog.ml.data.sparse.SparseMLData
-
- findInnovation(long) - Method in class org.encog.neural.neat.training.NEATInnovationList
-
Find an innovation for a single neuron.
- findInnovation(long, long) - Method in class org.encog.neural.neat.training.NEATInnovationList
-
Find an innovation for a new link added between two existing neurons.
- findInnovationSplit(long, long) - Method in class org.encog.neural.neat.training.NEATInnovationList
-
Find an innovation for a hidden neuron that split a existing link.
- findInputField(Class<?>, int) - Method in class org.encog.util.normalize.DataNormalization
-
Find an input field by its class.
- findLine(int, int[]) - Method in class org.encog.ml.bayesian.table.BayesianTable
-
Find the specified truth table line.
- findLink(String) - Method in class org.encog.bot.browse.WebPage
-
Find the link that contains the specified string.
- findNeuron(long) - Method in class org.encog.neural.neat.training.NEATGenome
-
Find the neuron with the specified nodeID.
- findNode(int) - Method in class org.encog.ml.prg.EncogProgram
-
Find the specified node by index.
- findNormalizedField(String, int) - Method in class org.encog.app.analyst.script.AnalystScript
-
Find the specified normalized field.
- findOccurance(String, String, int) - Static method in class org.encog.bot.BotUtil
-
Find the specified occurrence of one string in another string.
- findOpcode(String, int) - Method in enum org.encog.ml.prg.extension.EncogOpcodeRegistry
-
Find the specified opcode.
- findOpcodes(List<ValueType>, EncogProgramContext, boolean, boolean) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Find all opcodes that match the search criteria.
- findOperator(char, char) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
This method is used when parsing an expression.
- findOutputField(Class<?>, int) - Method in class org.encog.util.normalize.DataNormalization
-
Find an output field by its class.
- findStringInArray(String[], String) - Static method in class org.encog.util.EngineArray
-
Search for a string in an array.
- findTag(String, boolean) - Method in class org.encog.parse.tags.read.ReadXML
-
Advance until the specified tag is found.
- findTrans(Set<Trans>, UniverseCell) - Method in class org.encog.ca.program.generic.GenericCA
-
- findType(String, int) - Method in class org.encog.bot.browse.range.Form
-
Find the form input by type.
- findVariablesByTypes(List<ValueType>) - Method in class org.encog.ml.prg.EncogProgramContext
-
Find all of the variables of the specified types.
- finishNode - Variable in class org.encog.ml.schedule.ScheduleGraph
-
- finishTraining() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Called when training is finished.
- finishTraining() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Called when training is finished.
- finishTraining() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Called when training is finished.
- finishTraining() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- finishTraining() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- finishTraining() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
Should be called after training has completed and the iteration method
will not be called any further.
- finishTraining() - Method in class org.encog.ml.train.BasicTraining
-
Should be called after training has completed and the iteration method
will not be called any further.
- finishTraining() - Method in interface org.encog.ml.train.MLTrain
-
Should be called once training is complete and no more iterations are
needed.
- finishTraining() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Should be called after training has completed and the iteration method
will not be called any further.
- finishTraining() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Should be called after training has completed and the iteration method
will not be called any further.
- FIRST_LAMBDA - Static variable in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
The starting value for lambda.
- FIRST_SIGMA - Static variable in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
The starting value for sigma.
- fit(MLDataSet) - Method in class org.encog.ml.hmm.distributions.ContinousDistribution
-
Fit this distribution to the specified data set.
- fit(MLDataSet, double[]) - Method in class org.encog.ml.hmm.distributions.ContinousDistribution
-
Fit this distribution to the specified data set, given the specified
weights, per element.
- fit(MLDataSet) - Method in class org.encog.ml.hmm.distributions.DiscreteDistribution
-
Fit this distribution to the specified data.
- fit(MLDataSet, double[]) - Method in class org.encog.ml.hmm.distributions.DiscreteDistribution
-
Fit this distribution to the specified data, with weights.
- fit(MLDataSet) - Method in interface org.encog.ml.hmm.distributions.StateDistribution
-
Fit this distribution to the specified data set.
- fit(MLDataSet, double[]) - Method in interface org.encog.ml.hmm.distributions.StateDistribution
-
Fit this distribution to the specified data set, given the specified
weights, per element.
- FitnessObjective - Class in org.encog.ml.fitness
-
A fitness objective.
- FitnessObjective(double, CalculateScore) - Constructor for class org.encog.ml.fitness.FitnessObjective
-
Construct the fitness objective.
- FIVE - Static variable in class org.encog.mathutil.NumericRange
-
Display to five decimal places.
- FIVE_SPAN - Static variable in class org.encog.app.analyst.report.AnalystReport
-
Used as a col-span.
- fixFlatSpot(boolean) - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Default is true.
- fixSingleValue() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Fix normalized fields that have a single value for the min/max.
- fixSingleValue() - Method in class org.encog.util.arrayutil.NormalizedField
-
Fix normalized fields that have a single value for the min/max.
- flat - Variable in class org.encog.mathutil.matrices.hessian.BasicHessian
-
The flat network.
- FLAT_SPOT_CONST - Static variable in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
The constant to use to fix the flat spot problem.
- FlatLayer - Class in org.encog.neural.flat
-
Used to configure a flat layer.
- FlatLayer() - Constructor for class org.encog.neural.flat.FlatLayer
-
Do not use this constructor.
- FlatLayer(ActivationFunction, int, double) - Constructor for class org.encog.neural.flat.FlatLayer
-
Construct a flat layer.
- FlatNetwork - Class in org.encog.neural.flat
-
Implements a flat (vector based) neural network in the Encog Engine.
- FlatNetwork() - Constructor for class org.encog.neural.flat.FlatNetwork
-
Default constructor.
- FlatNetwork(FlatLayer[]) - Constructor for class org.encog.neural.flat.FlatNetwork
-
Create a flat network from an array of layers.
- FlatNetwork(int, int, int, int, boolean) - Constructor for class org.encog.neural.flat.FlatNetwork
-
Construct a flat neural network.
- FlatNetworkRBF - Class in org.encog.neural.flat
-
A flat network designed to handle an RBF.
- FlatNetworkRBF() - Constructor for class org.encog.neural.flat.FlatNetworkRBF
-
Default constructor.
- FlatNetworkRBF(int, int, int, RadialBasisFunction[]) - Constructor for class org.encog.neural.flat.FlatNetworkRBF
-
Construct an RBF flat network.
- flatten(DimensionConstraint) - Method in class org.encog.mathutil.dimension.MultiDimension
-
Flatten the multi-dimensional index into a single dimension index.
- flatten() - Method in class org.encog.ml.ea.population.BasicPopulation
-
Flatten the species into a single list of genomes.
- flatten() - Method in interface org.encog.ml.ea.population.Population
-
Flatten the species into a single list of genomes.
- flatToMatrix(double[], int, double[][]) - Method in class org.encog.neural.rbf.training.SVDTraining
-
- flush() - Method in class org.encog.persist.EncogWriteHelper
-
Flush the file.
- flushBase64() - Method in class org.encog.util.text.Base64.OutputStream
-
Method added by PHIL.
- fn(double[]) - Method in interface org.encog.mathutil.EncogFunction
-
- fn(double[]) - Method in class org.encog.neural.networks.training.nm.NelderMeadTraining
-
Calculate the error for the neural network with a given set of weights.
- fold(int) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Fold the dataset.
- FoldedDataSet - Class in org.encog.ml.data.folded
-
A folded data set allows you to "fold" the data into several equal(or nearly
equal) datasets.
- FoldedDataSet(MLDataSet) - Constructor for class org.encog.ml.data.folded.FoldedDataSet
-
Create a folded dataset.
- FoldedIterator - Class in org.encog.ml.data.folded
-
Used to iterate over a folded data set.
- FoldedIterator(FoldedDataSet) - Constructor for class org.encog.ml.data.folded.FoldedIterator
-
Construct the folded iterator.
- forceExtension(String, String) - Static method in class org.encog.util.file.FileUtil
-
- Form - Class in org.encog.bot.browse.range
-
A document range that represents a form, and all embedded tags.
- Form(WebPage) - Constructor for class org.encog.bot.browse.range.Form
-
Construct a form on the specified web page.
- Form.Method - Enum in org.encog.bot.browse.range
-
The method for this form.
- format(double, int) - Method in class org.encog.util.csv.CSVFormat
-
Format the specified number to a string with the specified number of
fractional digits.
- Format - Class in org.encog.util
-
Provides the ability for Encog to format numbers and times.
- format(LogRecord) - Method in class org.encog.util.logging.EncogFormatter
-
Format the log record.
- formatDouble(double, int) - Static method in class org.encog.util.Format
-
Format a double.
- formatEventName(BayesianEvent, int) - Static method in class org.encog.ml.bayesian.BayesianEvent
-
Format the event name with +, - and =.
- formatInteger(int) - Static method in class org.encog.util.Format
-
Format an integer.
- formatMemory(long) - Static method in class org.encog.util.Format
-
Format a memory amount, to something like 32 MB.
- formatNeuralData(MLData) - Static method in class org.encog.util.simple.EncogUtility
-
Format neural data as a list of numbers.
- formatPercent(double) - Static method in class org.encog.util.Format
-
Format a percent.
- formatPercentWhole(double) - Static method in class org.encog.util.Format
-
Format a percent with no decimal places.
- formatTimeSpan(int) - Static method in class org.encog.util.Format
-
Format a time span as seconds, minutes, hours and days.
- formatYesNo(boolean) - Static method in class org.encog.util.Format
-
Format a boolean as yes/no.
- FormElement - Class in org.encog.bot.browse.range
-
A document range that represents one individual component to a form.
- FormElement(WebPage) - Constructor for class org.encog.bot.browse.range.FormElement
-
Construct a form element from the specified web page.
- FormUtility - Class in org.encog.util.http
-
This class is used to construct responses to HTML forms.
- FormUtility(OutputStream, String) - Constructor for class org.encog.util.http.FormUtility
-
Prepare to access either a regular, or multipart, form.
- forward(DimensionConstraint) - Method in class org.encog.mathutil.dimension.MultiDimension
-
Roll the dimension forward by one.
- forward() - Method in class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
-
Roll the enumeration events forward by one.
- forward(ActionNode) - Method in class org.encog.ml.schedule.CalculateScheduleTimes
-
- ForwardBackwardCalculator - Class in org.encog.ml.hmm.alog
-
The forward-backward algorithm is an inference algorithm for hidden Markov
models which computes the posterior marginals of all hidden state variables
given a sequence of observations.
- ForwardBackwardCalculator() - Constructor for class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Construct an empty object.
- ForwardBackwardCalculator(MLDataSet, HiddenMarkovModel) - Constructor for class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Construct the forward/backward calculator.
- ForwardBackwardCalculator(MLDataSet, HiddenMarkovModel, EnumSet<ForwardBackwardCalculator.Computation>) - Constructor for class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Construct the object.
- ForwardBackwardCalculator.Computation - Enum in org.encog.ml.hmm.alog
-
- ForwardBackwardScaledCalculator - Class in org.encog.ml.hmm.alog
-
The forward-backward algorithm is an inference algorithm for hidden Markov
models which computes the posterior marginals of all hidden state variables
given a sequence of observations.
- ForwardBackwardScaledCalculator(MLDataSet, HiddenMarkovModel) - Constructor for class org.encog.ml.hmm.alog.ForwardBackwardScaledCalculator
-
- ForwardBackwardScaledCalculator(MLDataSet, HiddenMarkovModel, EnumSet<ForwardBackwardCalculator.Computation>) - Constructor for class org.encog.ml.hmm.alog.ForwardBackwardScaledCalculator
-
- FRAC_SHIFT - Static variable in class org.encog.util.text.DoubleString
-
- FreeformBackPropagation - Class in org.encog.neural.freeform.training
-
Perform backpropagation for a freeform neural network.
- FreeformBackPropagation(FreeformNetwork, MLDataSet, double, double) - Constructor for class org.encog.neural.freeform.training.FreeformBackPropagation
-
Construct a back propagation trainer.
- FreeformConnection - Interface in org.encog.neural.freeform
-
Defines a freeform connection between neurons.
- FreeformConnectionFactory - Interface in org.encog.neural.freeform.factory
-
A factory that creates connections.
- FreeformContextNeuron - Class in org.encog.neural.freeform
-
Defines a freeform context neuron.
- FreeformContextNeuron(FreeformNeuron) - Constructor for class org.encog.neural.freeform.FreeformContextNeuron
-
Construct the context neuron.
- FreeformLayer - Interface in org.encog.neural.freeform
-
Defines a freeform layer.
- FreeformLayerFactory - Interface in org.encog.neural.freeform.factory
-
A factory that creates layers.
- FreeformNetwork - Class in org.encog.neural.freeform
-
Implements a freefrom neural network.
- FreeformNetwork() - Constructor for class org.encog.neural.freeform.FreeformNetwork
-
Default constructor.
- FreeformNetwork(BasicNetwork) - Constructor for class org.encog.neural.freeform.FreeformNetwork
-
Craete a freeform network from a basic network.
- FreeformNetworkError - Exception in org.encog.neural.freeform
-
Freeform neural network error.
- FreeformNetworkError(String) - Constructor for exception org.encog.neural.freeform.FreeformNetworkError
-
Construct a message exception.
- FreeformNetworkError(String, Throwable) - Constructor for exception org.encog.neural.freeform.FreeformNetworkError
-
Construct an exception that holds another exception.
- FreeformNetworkError(Throwable) - Constructor for exception org.encog.neural.freeform.FreeformNetworkError
-
Construct an exception that holds another exception.
- FreeformNeuron - Interface in org.encog.neural.freeform
-
This interface defines a freeform neuron.
- FreeformNeuronFactory - Interface in org.encog.neural.freeform.factory
-
A factory that creates neurons.
- FreeformPropagationTraining - Class in org.encog.neural.freeform.training
-
Provides basic propagation functions to other trainers.
- FreeformPropagationTraining() - Constructor for class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Don't use this constructor, it is for serialization only.
- FreeformPropagationTraining(FreeformNetwork, MLDataSet) - Constructor for class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Construct the trainer.
- FreeformResilientPropagation - Class in org.encog.neural.freeform.training
-
- FreeformResilientPropagation(FreeformNetwork, MLDataSet) - Constructor for class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Construct the RPROP trainer, Use default intiial update and max step.
- FreeformResilientPropagation(FreeformNetwork, MLDataSet, double, double) - Constructor for class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Construct the RPROP trainer.
- fromList(CSVFormat, String) - Static method in class org.encog.util.csv.NumberList
-
Get an array of double's from a string of comma separated text.
- fromListInt(CSVFormat, String) - Static method in class org.encog.util.csv.NumberList
-
- fromPackedArray(double[], int) - Method in class org.encog.mathutil.matrices.Matrix
-
Create a matrix from a packed array.
- FrontierHolder - Class in org.encog.ml.graph.search
-
- FrontierHolder(Prioritizer) - Constructor for class org.encog.ml.graph.search.FrontierHolder
-
- function(int, int) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodBubble
-
Determine how much the current neuron should be affected by training
based on its proximity to the winning neuron.
- function(int, int) - Method in interface org.encog.neural.som.training.basic.neighborhood.NeighborhoodFunction
-
Determine how much the current neuron should be affected by training
based on its proximity to the winning neuron.
- function(int, int) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF
-
Calculate the value for the multi RBF function.
- function(int, int) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF1D
-
Determine how much the current neuron should be affected by training
based on its proximity to the winning neuron.
- function(int, int) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodSingle
-
Determine how much the current neuron should be affected by training
based on its proximity to the winning neuron.
- FunctionFactory - Class in org.encog.ml.prg.extension
-
A function factory maps the opcodes contained in the EncogOpcodeRegistry into
an EncogProgram.
- FunctionFactory() - Constructor for class org.encog.ml.prg.extension.FunctionFactory
-
Default constructor.
- gamma - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- GaussianFitting - Class in org.encog.ml.fitting.gaussian
-
- GaussianFitting(int) - Constructor for class org.encog.ml.fitting.gaussian.GaussianFitting
-
- GaussianFunction - Class in org.encog.mathutil.rbf
-
Multi-dimensional gaussian function.
- GaussianFunction() - Constructor for class org.encog.mathutil.rbf.GaussianFunction
-
Default constructor, used for reflection.
- GaussianFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.GaussianFunction
-
Construct a single-dimension Gaussian function with the specified peak,
centers and widths.
- GaussianFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.GaussianFunction
-
Construct a multi-dimension Gaussian function with the specified peak,
centers and widths.
- GaussianFunction(int) - Constructor for class org.encog.mathutil.rbf.GaussianFunction
-
Create centered at zero, width 0, and peak 0.
- GaussianRandomizer - Class in org.encog.mathutil.randomize
-
Generally, you will not want to use this randomizer as a pure neural network
randomizer.
- GaussianRandomizer(double, double) - Constructor for class org.encog.mathutil.randomize.GaussianRandomizer
-
Construct a Gaussian randomizer.
- generate(EncogAnalyst) - Method in class org.encog.app.generate.EncogCodeGeneration
-
Generate the code from Encog Analyst.
- generate(File, File) - Method in class org.encog.app.generate.EncogCodeGeneration
-
Generate from a method and data.
- generate(EncogAnalyst) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Generate based on the provided Encog Analyst.
- generate(EncogGenProgram, boolean) - Method in class org.encog.app.generate.generators.cs.GenerateCS
-
- generate(EncogGenProgram, boolean) - Method in class org.encog.app.generate.generators.java.GenerateEncogJava
-
- generate(EncogGenProgram, boolean) - Method in class org.encog.app.generate.generators.js.GenerateEncogJavaScript
-
- generate(EncogGenProgram, boolean) - Method in interface org.encog.app.generate.generators.ProgramGenerator
-
- generate(EncogAnalyst) - Method in interface org.encog.app.generate.generators.TemplateGenerator
-
Generate the template based on Encog Analyst script.
- generate(Random) - Method in class org.encog.mathutil.randomize.RandomChoice
-
Generate a random choice, based on the probabilities provided to the constructor.
- generate(Random, int) - Method in class org.encog.mathutil.randomize.RandomChoice
-
Generate a random choice, but skip one of the choices.
- generate() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Generate the training sets.
- generate(Random) - Method in interface org.encog.ml.ea.population.PopulationGenerator
-
Generate a random genome.
- generate(Random, Population) - Method in interface org.encog.ml.ea.population.PopulationGenerator
-
Generate a random population.
- generate() - Method in class org.encog.ml.hmm.distributions.ContinousDistribution
-
Generate a random data pair, based on the probabilities.
- generate() - Method in class org.encog.ml.hmm.distributions.DiscreteDistribution
-
Generate a random sequence.
- generate() - Method in interface org.encog.ml.hmm.distributions.StateDistribution
-
Generate a random data pair, based on the probabilities.
- generate(Random) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Generate a random genome.
- generate(Random, Population) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Generate a random population.
- generate() - Method in class org.encog.neural.pattern.ADALINEPattern
-
Generate the network.
- generate() - Method in class org.encog.neural.pattern.ART1Pattern
-
Generate the neural network.
- generate() - Method in class org.encog.neural.pattern.BAMPattern
-
- generate() - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Generate the network.
- generate() - Method in class org.encog.neural.pattern.CPNPattern
-
Generate the network.
- generate() - Method in class org.encog.neural.pattern.ElmanPattern
-
Generate the Elman neural network.
- generate() - Method in class org.encog.neural.pattern.FeedForwardPattern
-
Generate the feedforward neural network.
- generate() - Method in class org.encog.neural.pattern.HopfieldPattern
-
Generate the Hopfield neural network.
- generate() - Method in class org.encog.neural.pattern.JordanPattern
-
Generate a Jordan neural network.
- generate() - Method in interface org.encog.neural.pattern.NeuralNetworkPattern
-
Generate the specified neural network.
- generate() - Method in class org.encog.neural.pattern.PNNPattern
-
Generate the RSOM network.
- generate() - Method in class org.encog.neural.pattern.RadialBasisPattern
-
Generate the RBF network.
- generate() - Method in class org.encog.neural.pattern.SOMPattern
-
Generate the RSOM network.
- generate() - Method in class org.encog.neural.pattern.SVMPattern
-
- generate(long, int, int, int, double, double) - Static method in class org.encog.util.benchmark.RandomTrainingFactory
-
Generate a random training set.
- generate(MLDataSet, long, int, double, double) - Static method in class org.encog.util.benchmark.RandomTrainingFactory
-
Generate random training into a training set.
- generate() - Method in class org.encog.util.identity.BasicGenerateID
-
Generate the next ID.
- generate() - Method in interface org.encog.util.identity.GenerateID
-
Generate the next ID.
- GENERATE_CONFIG_SOURCE_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "GENERATE:CONFIG_sourceFile".
- GENERATE_CONFIG_TARGET_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "GENERATE:CONFIG_targetFile".
- generateActivationFactory(String, ActivationFunction) - Static method in class org.encog.util.obj.ActivationUtil
-
- GenerateCS - Class in org.encog.app.generate.generators.cs
-
- GenerateCS() - Constructor for class org.encog.app.generate.generators.cs.GenerateCS
-
- GenerateEncogJava - Class in org.encog.app.generate.generators.java
-
- GenerateEncogJava() - Constructor for class org.encog.app.generate.generators.java.GenerateEncogJava
-
- GenerateEncogJavaScript - Class in org.encog.app.generate.generators.js
-
- GenerateEncogJavaScript() - Constructor for class org.encog.app.generate.generators.js.GenerateEncogJavaScript
-
- generateEPL() - Method in class org.encog.ml.prg.EncogProgram
-
- generateForwardBackwardCalculator(MLDataSet, HiddenMarkovModel) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- generateForwardBackwardCalculator(MLDataSet, HiddenMarkovModel) - Method in class org.encog.ml.hmm.train.bw.TrainBaumWelch
-
- generateForwardBackwardCalculator(MLDataSet, HiddenMarkovModel) - Method in class org.encog.ml.hmm.train.bw.TrainBaumWelchScaled
-
- GenerateID - Interface in org.encog.util.identity
-
Interface that defines a unique ID generator.
- generateInputForPrediction(Date) - Method in class org.encog.ml.data.market.MarketMLDataSet
-
To be implemented later.
- generateInputNeuralData(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Generate input neural data for the specified index.
- generateLoadTraining(File) - Method in class org.encog.app.generate.program.EncogProgramNode
-
Load the training data.
- GenerateMQL4 - Class in org.encog.app.generate.generators.mql4
-
- GenerateMQL4() - Constructor for class org.encog.app.generate.generators.mql4.GenerateMQL4
-
- GenerateNinjaScript - Class in org.encog.app.generate.generators.ninja
-
- GenerateNinjaScript() - Constructor for class org.encog.app.generate.generators.ninja.GenerateNinjaScript
-
- generateOutputNeuralData(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Generate neural ideal data for the specified index.
- GenerateRandom - Interface in org.encog.mathutil.randomize.generate
-
Interface that defines how random numbers are generated.
- generateRandom(int...) - Method in class org.encog.ml.bayesian.table.BayesianTable
-
Generate a random sampling based on this truth table.
- generateRandomOpcode(Random, List<ProgramExtensionTemplate>) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
Generate a random opcode.
- generateSequences(int, int) - Method in class org.encog.ml.hmm.alog.MarkovGenerator
-
- generateSingleDataRange(EncogFunction, double, double, double) - Static method in class org.encog.util.data.GenerationUtil
-
- generateTable(BayesianEvent) - Static method in class org.encog.ml.bayesian.bif.BIFUtil
-
Generate a table, in BIF format.
- generateTraining(int, boolean) - Static method in class org.encog.util.benchmark.EncoderTrainingFactory
-
Generate an encoder training set over the range [0.0,1.0].
- generateTraining(int, boolean, double, double) - Static method in class org.encog.util.benchmark.EncoderTrainingFactory
-
Generate an encoder over the specified range.
- generateTraining(int, boolean, double, double, double, double) - Static method in class org.encog.util.benchmark.EncoderTrainingFactory
-
- GenerateWorker - Class in org.encog.ml.prg.generator
-
Used to thread the generation process.
- GenerateWorker(AbstractPrgGenerator, PrgPopulation) - Constructor for class org.encog.ml.prg.generator.GenerateWorker
-
Construct the worker.
- GenerationUtil - Class in org.encog.util.data
-
Utility class used to create training data from a function.
- GenerationUtil() - Constructor for class org.encog.util.data.GenerationUtil
-
- GenericCA - Class in org.encog.ca.program.generic
-
- GenericCA() - Constructor for class org.encog.ca.program.generic.GenericCA
-
- GenericCA(Universe, int) - Constructor for class org.encog.ca.program.generic.GenericCA
-
- GenericEnsembleML - Class in org.encog.ensemble
-
- GenericEnsembleML(MLMethod, String) - Constructor for class org.encog.ensemble.GenericEnsembleML
-
- GenericIO - Class in org.encog.ca.program.generic
-
- GenericIO() - Constructor for class org.encog.ca.program.generic.GenericIO
-
- GeneticCODEC - Interface in org.encog.ml.ea.codec
-
A CODEC defines how to transfer between a genome and phenome.
- GeneticError - Exception in org.encog.ml.genetic
-
An error raised by the genetic algorithm.
- GeneticError(String) - Constructor for exception org.encog.ml.genetic.GeneticError
-
Construct a message exception.
- GeneticError(String, Throwable) - Constructor for exception org.encog.ml.genetic.GeneticError
-
Construct an exception that holds another exception.
- GeneticError(Throwable) - Constructor for exception org.encog.ml.genetic.GeneticError
-
Construct an exception that holds another exception.
- GeneticFactory - Class in org.encog.ml.factory.train
-
A factory to create genetic algorithm trainers.
- GeneticFactory() - Constructor for class org.encog.ml.factory.train.GeneticFactory
-
- Genome - Interface in org.encog.ml.ea.genome
-
A genome is the basic blueprint for creating an phenome (organism) in Encog.
- GenomeAsPhenomeCODEC - Class in org.encog.ml.ea.codec
-
This is a simple pass-through CODEC.
- GenomeAsPhenomeCODEC() - Constructor for class org.encog.ml.ea.codec.GenomeAsPhenomeCODEC
-
- GenomeComparator - Interface in org.encog.ml.ea.sort
-
Defines methods for comparing genomes.
- GenomeFactory - Interface in org.encog.ml.ea.genome
-
Defines a factory that produces genomes.
- get(int) - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- get(int) - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- get(int, int) - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- get(int, int) - Method in interface org.encog.ca.universe.Universe
-
- get(int) - Method in interface org.encog.ca.universe.UniverseCell
-
- get(int) - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- get(int, int) - Method in class org.encog.mathutil.matrices.Matrix
-
Read the specified cell in the matrix.
- get(String) - Method in class org.encog.mathutil.probability.vars.VariableList
-
- get(int) - Method in class org.encog.mathutil.probability.vars.VariableList
-
- get(int) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- get(int) - Method in class org.encog.ml.data.basic.BasicMLDataSet
- get(int) - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
- get(int) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- get(int) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- get(int) - Method in interface org.encog.ml.data.MLDataSet
-
- get(int) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
- get(int) - Method in class org.encog.ml.kmeans.BasicCluster
-
Get the specified data item by index.
- get(int) - Method in interface org.encog.ml.MLCluster
-
Get the specified data item by index.
- get(String) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
-
Get an object by name.
- get(int) - Method in class org.encog.util.csv.ReadCSV
-
Get the specified column as a string.
- get(String) - Method in class org.encog.util.csv.ReadCSV
-
Get the column by its string name, as a string.
- get(int) - Method in class org.encog.util.kmeans.KMeansUtil
-
Get a cluster by index.
- getA() - Method in class org.encog.util.ObjectPair
-
- getA1() - Method in class org.encog.neural.art.ART1
-
- getA1() - Method in class org.encog.neural.pattern.ART1Pattern
-
- getAction() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getAction() - Method in class org.encog.app.analyst.script.preprocess.FieldPreprocess
-
- getAction() - Method in class org.encog.bot.browse.range.Form
-
- getAction() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getAction() - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- getActions() - Method in class org.encog.ml.world.basic.BasicWorld
-
- getActions() - Method in interface org.encog.ml.world.World
-
- getActivation() - Method in class org.encog.neural.flat.FlatLayer
-
- getActivation() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
- getActivation() - Method in interface org.encog.neural.freeform.FreeformNeuron
-
- getActivation(int) - Method in class org.encog.neural.networks.BasicNetwork
-
Get the activation function for the specified layer.
- getActivationCycles() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getActivationCycles() - Method in class org.encog.neural.neat.NEATNetwork
-
- getActivationCycles() - Method in class org.encog.neural.neat.NEATPopulation
-
- getActivationFunction() - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- getActivationFunction() - Method in class org.encog.neural.freeform.basic.BasicActivationSummation
- getActivationFunction() - Method in interface org.encog.neural.freeform.InputSummation
-
- getActivationFunction() - Method in class org.encog.neural.neat.training.NEATNeuronGene
-
- getActivationFunction() - Method in class org.encog.neural.networks.layers.BasicLayer
-
- getActivationFunction() - Method in interface org.encog.neural.networks.layers.Layer
-
- getActivationFunctions() - Method in class org.encog.neural.flat.FlatNetwork
-
- getActivationFunctions() - Method in class org.encog.neural.neat.NEATNetwork
-
- getActivationFunctions() - Method in class org.encog.neural.neat.NEATPopulation
-
- getActivationOutput() - Method in class org.encog.neural.pattern.FeedForwardPattern
-
- getActualHigh() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getActualHigh() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getActualLow() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getActualLow() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getActualMax() - Method in class org.encog.ml.data.auto.AutoFloatColumn
-
- getActualMin() - Method in class org.encog.ml.data.auto.AutoFloatColumn
-
- getAdd1() - Method in class org.encog.ca.program.generic.Trans
-
- getAdd2() - Method in class org.encog.ca.program.generic.Trans
-
- getAdjacentStates(GridState) - Method in class org.encog.ml.world.grid.GridWorld
-
- getAdjustedScore() - Method in class org.encog.ml.ea.genome.BasicGenome
-
- getAdjustedScore() - Method in interface org.encog.ml.ea.genome.Genome
-
Get the adjusted score, this considers old-age penalties and youth
bonuses.
- getAdjusters() - Method in class org.encog.ml.ea.score.parallel.ParallelScore
-
- getAge() - Method in class org.encog.ml.ea.species.BasicSpecies
- getAge() - Method in interface org.encog.ml.ea.species.Species
-
- getAgents() - Method in class org.encog.ml.world.basic.BasicWorld
-
- getAgents() - Method in interface org.encog.ml.world.World
-
- getAggregator() - Method in class org.encog.ensemble.Ensemble
-
- getAllFields(Class<?>) - Static method in class org.encog.util.obj.ReflectionUtil
-
Get all of the fields from the specified class as a collection.
- getAllFields(Class<?>, Collection<Field>) - Static method in class org.encog.util.obj.ReflectionUtil
-
Get all of the fields in the specified class and super classes.
- getAllValues() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getAnalyst() - Method in class org.encog.app.analyst.commands.Cmd
-
- getAnalyst() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getAnalyst() - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
- getAnalyzedClassMembers() - Method in class org.encog.app.analyst.analyze.AnalyzedField
-
Get the class members.
- getAnnealCycles() - Method in class org.encog.neural.pattern.BoltzmannPattern
-
- getAnnealCycles() - Method in class org.encog.neural.thermal.BoltzmannMachine
-
- getArgCount() - Method in class org.encog.app.analyst.script.ml.ScriptOpcode
-
- getArgs() - Method in class org.encog.app.generate.program.EncogProgramNode
-
- getArgs(BayesianNetwork) - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
Get the arguments to this event.
- getArguments() - Method in class org.encog.ml.bayesian.table.TableLine
-
- getArray() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Subclasses must provide access to an array that makes up the solution.
- getArray() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
Get the network as an array of doubles.
- getArray() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper
-
Used to pass the getArray call on to the parent object.
- getArray() - Method in class org.encog.util.normalize.target.NormalizationStorageArray1D
-
- getArray() - Method in class org.encog.util.normalize.target.NormalizationStorageArray2D
-
- getArrayCopy() - Method in class org.encog.mathutil.matrices.Matrix
-
- getArrayCopy() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Get a copy of the array.
- getArrayCopy() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
- getArrayCopy() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper
-
Used to pass the getArrayCopy call on to the parent object.
- getAttributeInt(String) - Method in class org.encog.parse.tags.Tag
-
Get the specified attribute as an integer.
- getAttributes() - Method in class org.encog.bot.rss.RSS
-
Get the list of attributes.
- getAttributes() - Method in class org.encog.parse.tags.Tag
-
Get a map of all attributes.
- getAttributeValue(String) - Method in class org.encog.parse.tags.Tag
-
Get the value of the specified attribute.
- getAvg() - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- getAvg() - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- getAvg() - Method in interface org.encog.ca.universe.UniverseCell
-
- getB() - Method in class org.encog.util.ObjectPair
-
- getB1() - Method in class org.encog.neural.art.ART1
-
- getB1() - Method in class org.encog.neural.pattern.ART1Pattern
-
- getBackConnections() - Method in class org.encog.ml.graph.BasicNode
-
- getBackwardWindowSize() - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- getBaseDataset() - Method in class org.encog.ml.data.cross.KFoldCrossvalidation
-
- getBaseEvents() - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
- getBaseHeader(int) - Method in class org.encog.app.analyst.util.CSVHeaders
-
Get the base header, strip any (...).
- getBasePath() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getBatchSize() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
- getBatchSize() - Method in interface org.encog.neural.networks.training.BatchSize
-
The batch size.
- getBatchSize() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
The batch size.
- getBegin() - Method in class org.encog.bot.browse.range.DocumentRange
-
- getBeginningIndex() - Method in class org.encog.app.quant.indicators.Indicator
-
- getBeginTraining() - Method in class org.encog.neural.flat.FlatNetwork
-
- getBestComparator() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Get the comparator that is used to choose the "true best" genome.
- getBestComparator() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Get the comparator that is used to choose the "true best" genome.
- getBestConst() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getBestGamma() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getBestGenome() - Method in class org.encog.ml.ea.population.BasicPopulation
- getBestGenome() - Method in interface org.encog.ml.ea.population.Population
-
- getBestGenome() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getBestGenome() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getBestNetwork() - Method in class org.encog.neural.prune.PruneIncremental
-
- getBestScore() - Method in class org.encog.ml.ea.species.BasicSpecies
- getBestScore() - Method in interface org.encog.ml.ea.species.Species
-
- getBias() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getBiasActivation() - Method in class org.encog.neural.flat.FlatLayer
-
- getBiasActivation() - Method in class org.encog.neural.flat.FlatNetwork
-
- getBiasActivation() - Method in interface org.encog.neural.networks.layers.Layer
-
Most layer types will default this value to one.
- getBiasedNodes() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getBiasValues() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getBinaryScore() - Method in class org.encog.util.benchmark.EncogBenchmark
-
- getBirthGeneration() - Method in class org.encog.ml.ea.genome.BasicGenome
-
- getBirthGeneration() - Method in interface org.encog.ml.ea.genome.Genome
-
- getBoolean(int) - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Get the specified data item as a boolean.
- getBoolean(String, boolean, boolean) - Method in class org.encog.util.ParamsHolder
-
Get a param as a boolean.
- getBoundary() - Static method in class org.encog.util.http.FormUtility
-
Generate a boundary for a multipart form.
- getBuffer() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getBufferSize() - Method in class org.encog.app.analyst.csv.shuffle.ShuffleCSV
-
- getC() - Method in class org.encog.ml.svm.training.SVMTrain
-
- getC1() - Method in class org.encog.neural.art.ART1
-
- getC1() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Get the cognition coefficient (c1).
- getC1() - Method in class org.encog.neural.pattern.ART1Pattern
-
- getC2() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Get the social coefficient (c2).
- getCalculatedFields() - Method in class org.encog.app.analyst.script.preprocess.AnalystPreprocess
-
- getCalculatedIdealSize() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- getCalculatedInputSize() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- getCalculateScore() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
- getCalculation() - Method in class org.encog.app.analyst.script.preprocess.FieldPreprocess
-
- getCatchAll() - Method in class org.encog.util.normalize.output.mapped.OutputFieldEncode
-
- getCellFactory() - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- getCellFactory() - Method in interface org.encog.ca.universe.Universe
-
- getCenter() - Method in class org.encog.engine.network.activation.ActivationStep
-
- getCenter(int) - Method in class org.encog.mathutil.rbf.BasicRBF
-
Get the center of this RBD.
- getCenter(int) - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
Get the center of this RBD.
- getCenters() - Method in class org.encog.mathutil.rbf.BasicRBF
- getCenters() - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
- getCentroid() - Method in class org.encog.ml.kmeans.BasicCluster
-
- getChampMutation() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getChildEvent() - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
- getChildNode(int) - Method in class org.encog.ml.prg.ProgramNode
-
Get the specified child node.
- getChildNodeCount() - Method in class org.encog.ml.prg.extension.BasicTemplate
- getChildNodeCount() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- getChildNodes() - Method in class org.encog.ml.tree.basic.BasicTreeNode
-
- getChildNodes() - Method in interface org.encog.ml.tree.TreeNode
-
- getChildren() - Method in class org.encog.app.generate.program.EncogTreeNode
-
- getChildren() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- getChoice(int) - Method in class org.encog.ml.bayesian.BayesianEvent
-
Return the choice specified by the index.
- getChoices() - Method in class org.encog.mathutil.probability.vars.RandomVariable
-
- getChoices() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- getClassAttribute() - Method in class org.encog.bot.browse.range.DocumentRange
-
- getClassCount() - Method in class org.encog.mathutil.probability.CalcProbability
-
- getClasses() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getClasses() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getClasses() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getClassificationStructure() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- getClassificationTarget() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Get the classification target.
- getClassificationTargetEvent() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- getClassMembers() - Method in class org.encog.app.analyst.script.DataField
-
- getClScore() - Method in class org.encog.util.benchmark.EncogBenchmark
-
- getCluster(int) - Method in class org.encog.util.kmeans.KMeansUtil
-
Get a cluster by index.
- getClusters() - Method in class org.encog.ml.kmeans.KMeansClustering
-
- getClusters() - Method in interface org.encog.ml.MLClustering
-
- getCode() - Method in class org.encog.app.analyst.script.AnalystClassItem
-
- getCode() - Method in class org.encog.bot.dataunit.CodeDataUnit
-
- getCodec() - Method in class org.encog.ml.data.buffer.BinaryDataLoader
-
- getCodec() - Method in class org.encog.ml.data.buffer.MemoryDataLoader
-
- getCodec() - Method in class org.encog.ml.ea.score.parallel.ParallelScore
-
- getCODEC() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getCODEC() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getCODEC() - Method in class org.encog.neural.neat.NEATPopulation
-
- getCodeTargetLanguage() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getCol(int) - Method in class org.encog.mathutil.matrices.Matrix
-
Read one entire column from the matrix as a sub-matrix.
- getCols() - Method in class org.encog.mathutil.matrices.Matrix
-
Get the columns in the matrix.
- getColumn() - Method in class org.encog.ml.world.grid.GridState
-
- getColumnCount() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getColumnCount() - Method in class org.encog.util.csv.ReadCSV
-
Get the column count.
- getColumnData(String, ReadCSV) - Method in class org.encog.app.analyst.csv.basic.BasicCachedFile
-
Get the data for a specific column.
- getColumnMapping() - Method in class org.encog.app.analyst.csv.basic.BasicCachedFile
-
- getColumnmMovement() - Method in class org.encog.ca.program.basic.Movement
-
- getColumnNames() - Method in class org.encog.util.csv.ReadCSV
-
- getColumns() - Method in class org.encog.app.analyst.csv.basic.BasicCachedFile
-
- getColumns() - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- getColumns() - Method in interface org.encog.ca.universe.Universe
-
- getColumns() - Method in class org.encog.ml.world.grid.GridWorld
-
- getColumnsNeeded() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getColumnsNeeded() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getCommand() - Method in class org.encog.app.analyst.script.process.ProcessField
-
- getCompareValue() - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- getCompatibilityScore(Genome, Genome) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
Determine how compatible two genomes are.
- getCompatibilityScore(Genome, Genome) - Method in class org.encog.ml.prg.species.PrgSpeciation
-
Determine how compatible two genomes are.
- getCompatibilityScore(Genome, Genome) - Method in class org.encog.neural.neat.training.species.OriginalNEATSpeciation
-
Determine how compatible two genomes are.
- getCompatibilityThreshold() - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- getComplexData() - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
- getComplexData(int) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Get the complex data at the specified index.
- getComplexData() - Method in interface org.encog.ml.data.MLComplexData
-
- getComplexData(int) - Method in interface org.encog.ml.data.MLComplexData
-
Get the complex data at the specified index.
- getComplexityFullPenalty() - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- getComplexityPenalty() - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- getComplexityPenaltyThreshold() - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- getComplexityPentaltyFullThreshold() - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- getComponents() - Method in class org.encog.ml.ea.opp.CompoundOperator
-
- getConnectionLimit() - Method in class org.encog.neural.flat.FlatNetwork
-
- getConnectionLimit() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
- getConnections() - Method in class org.encog.ml.graph.BasicNode
-
- getConstBegin() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getConstDisjoint() - Method in class org.encog.neural.neat.training.species.OriginalNEATSpeciation
-
- getConstEnd() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getConstExcess() - Method in class org.encog.neural.neat.training.species.OriginalNEATSpeciation
-
- getConstMatched() - Method in class org.encog.neural.neat.training.species.OriginalNEATSpeciation
-
- getConstraintRules() - Method in class org.encog.ml.ea.rules.BasicRuleHolder
- getConstraintRules() - Method in interface org.encog.ml.ea.rules.RuleHolder
-
- getConstStep() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getContents() - Method in class org.encog.app.generate.generators.AbstractGenerator
-
Get the contents.
- getContents() - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
- getContents() - Method in interface org.encog.app.generate.generators.LanguageSpecificGenerator
-
- getContents() - Method in class org.encog.bot.browse.WebPage
-
- getContents() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- getContents() - Method in class org.encog.ml.graph.search.FrontierHolder
-
- getContents() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
-
- getContents() - Method in class org.encog.util.kmeans.Cluster
-
- getContext() - Method in class org.encog.ml.prg.EncogProgram
-
- getContext() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getContext() - Method in class org.encog.ml.prg.train.PrgPopulation
-
- getContextCount() - Method in class org.encog.neural.flat.FlatLayer
-
- getContextFedBy() - Method in class org.encog.neural.flat.FlatLayer
-
- getContextSource() - Method in class org.encog.neural.freeform.FreeformContextNeuron
-
- getContextTargetOffset() - Method in class org.encog.neural.flat.FlatNetwork
-
- getContextTargetSize() - Method in class org.encog.neural.flat.FlatNetwork
-
- getCost() - Method in class org.encog.ml.graph.BasicEdge
-
- getCost(BasicNode) - Method in class org.encog.ml.graph.BasicNode
-
- getCount() - Method in class org.encog.app.analyst.script.AnalystClassItem
-
- getCount() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getCount() - Method in class org.encog.ml.data.versatile.division.DataDivision
-
- getCount() - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- getCount() - Method in class org.encog.neural.flat.FlatLayer
-
- getCount() - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
- getCount(String) - Method in class org.encog.util.text.BagOfWords
-
- getCountPer() - Method in class org.encog.neural.pnn.BasicPNN
-
- getCounts() - Method in class org.encog.app.analyst.csv.balance.BalanceCSV
-
- getCovariance() - Method in class org.encog.ml.hmm.distributions.ContinousDistribution
-
- getCpuScore() - Method in class org.encog.util.benchmark.EncogBenchmark
-
- getCSVFormat() - Method in class org.encog.util.normalize.DataNormalization
-
- getCurrentBlue() - Method in class org.encog.util.downsample.RGBDownsample
-
- getCurrentFlatNetwork() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
- getCurrentFold() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- getCurrentFoldOffset() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- getCurrentFoldSize() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- getCurrentGreen() - Method in class org.encog.util.downsample.RGBDownsample
-
- getCurrentID() - Method in class org.encog.util.identity.BasicGenerateID
-
- getCurrentID() - Method in interface org.encog.util.identity.GenerateID
-
- getCurrentIndex() - Method in class org.encog.util.normalize.segregate.index.IndexSegregator
-
- getCurrentLevel() - Method in class org.encog.ml.prg.opp.LevelHolder
-
- getCurrentLevel() - Method in class org.encog.util.logging.EncogLogging
-
- getCurrentPage() - Method in class org.encog.bot.browse.Browser
-
- getCurrentRed() - Method in class org.encog.util.downsample.RGBDownsample
-
- getCurrentSection() - Method in class org.encog.persist.EncogWriteHelper
-
- getCurrentState() - Method in class org.encog.ml.hmm.alog.MarkovGenerator
-
- getCurrentState() - Method in class org.encog.ml.world.basic.BasicAgent
-
- getCurrentState() - Method in interface org.encog.ml.world.WorldAgent
-
- getCurrentState() - Method in class org.encog.neural.thermal.ThermalNetwork
-
- getCurrentValue() - Method in class org.encog.util.normalize.input.BasicInputField
-
- getCurrentValue() - Method in interface org.encog.util.normalize.input.InputField
-
- getCycles() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- getD() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition
-
Return the block diagonal eigenvalue matrix
- getD1() - Method in class org.encog.neural.art.ART1
-
- getD1() - Method in class org.encog.neural.pattern.ART1Pattern
-
- getData() - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
- getData() - Method in class org.encog.app.analyst.csv.basic.LoadedRow
-
- getData() - Method in class org.encog.app.quant.util.BarBuffer
-
- getData() - Method in class org.encog.bot.browse.WebPage
-
- getData() - Method in class org.encog.mathutil.matrices.Matrix
-
- getData() - Method in class org.encog.ml.data.auto.AutoFloatColumn
-
- getData() - Method in class org.encog.ml.data.basic.BasicMLComplexData
- getData(int) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Get the element specified index value.
- getData() - Method in class org.encog.ml.data.basic.BasicMLData
- getData(int) - Method in class org.encog.ml.data.basic.BasicMLData
-
Get the element specified index value.
- getData() - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
Get the data held by this container.
- getData(MarketDataType) - Method in class org.encog.ml.data.market.loader.LoadedMarketData
-
Get one type of market data from this date.
- getData() - Method in interface org.encog.ml.data.MLData
-
- getData(int) - Method in interface org.encog.ml.data.MLData
-
Get the element specified index value.
- getData() - Method in class org.encog.ml.data.sparse.SparseMLData
- getData(int) - Method in class org.encog.ml.data.sparse.SparseMLData
-
Get the element specified index value.
- getData() - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Get the data held by this object as an array of doubles.
- getData(int) - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Get the data held by the index.
- getData() - Method in class org.encog.ml.data.temporal.TemporalPoint
-
- getData(int) - Method in class org.encog.ml.data.temporal.TemporalPoint
-
Get the data at the specified index.
- getData() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- getData() - Method in class org.encog.ml.genetic.genome.DoubleArrayGenome
-
- getData() - Method in class org.encog.ml.genetic.genome.IntegerArrayGenome
-
- getData() - Method in class org.encog.ml.graph.EuclideanNode
-
- getData() - Method in class org.encog.ml.kmeans.BasicCluster
- getData() - Method in interface org.encog.ml.MLCluster
-
- getData() - Method in class org.encog.ml.prg.ProgramNode
-
- getData() - Method in class org.encog.util.datastruct.WindowInt
-
- getDataset() - Method in class org.encog.ml.data.versatile.division.DataDivision
-
- getDataset() - Method in class org.encog.ml.model.EncogModel
-
- getDataset() - Method in class org.encog.util.normalize.target.NormalizationStorageNeuralDataSet
-
- getDataSetSize() - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- getDataSize() - Method in class org.encog.bot.browse.WebPage
-
Get the number of data items in this collection.
- getDataSize() - Method in class org.encog.ml.prg.extension.BasicTemplate
- getDataSize() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- getDataType() - Method in class org.encog.ml.data.market.MarketDataDescription
-
- getDataType() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getDataUnit(int) - Method in class org.encog.bot.browse.WebPage
-
Get the DataUnit unit at the specified index.
- getDate() - Method in class org.encog.bot.rss.RSSItem
-
Get the publication date.
- getDate(String) - Method in class org.encog.util.csv.ReadCSV
-
Get the column as a date.
- GetDayOfWeek(long) - Static method in class org.encog.util.time.NumericDateUtil
-
- getDecimal() - Method in class org.encog.util.csv.CSVFormat
-
- getDecimalCharacter() - Static method in class org.encog.util.csv.CSVFormat
-
Get the decimal character currently in use by the computer's default
location.
- getDefinedVariables() - Method in class org.encog.ml.prg.EncogProgramContext
-
- getDeriv() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getDeriv2() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getDerivative() - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
- getDescription() - Method in class org.encog.bot.rss.RSSItem
-
Get the description.
- getDescription() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Get a description of all the current settings.
- getDescriptions() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getDesiredSetSize() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getDestinationNode() - Method in class org.encog.ml.graph.BasicPath
-
- getDeterminant() - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition
-
- getDimension(int) - Method in class org.encog.mathutil.dimension.MultiDimension
-
Get a dimension.
- getDimensions() - Method in class org.encog.mathutil.dimension.MultiDimension
-
- getDimensions() - Method in class org.encog.mathutil.rbf.BasicRBF
- getDimensions() - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
- getDimensions() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getDisabledConnections() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getDistance(double[], int) - Method in class org.encog.mathutil.Equilateral
-
Get the Euclidean distance between the specified data and the set number.
- getDouble(int) - Method in class org.encog.util.csv.ReadCSV
-
Get the column as a double specified by index.
- getDouble(String) - Method in class org.encog.util.csv.ReadCSV
-
Get the specified column as a double.
- getDouble(String, boolean, double) - Method in class org.encog.util.ParamsHolder
-
Get a param as a double.
- getDoublePivot() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Return pivot permutation vector as a one-dimensional double array
- getDownSampleBottom() - Method in interface org.encog.util.downsample.Downsample
-
- getDownSampleBottom() - Method in class org.encog.util.downsample.RGBDownsample
-
- getDownSampleLeft() - Method in interface org.encog.util.downsample.Downsample
-
- getDownSampleLeft() - Method in class org.encog.util.downsample.RGBDownsample
-
- getDownSampleRight() - Method in interface org.encog.util.downsample.Downsample
-
- getDownSampleRight() - Method in class org.encog.util.downsample.RGBDownsample
-
- getDownSampleTop() - Method in interface org.encog.util.downsample.Downsample
-
- getDownSampleTop() - Method in class org.encog.util.downsample.RGBDownsample
-
- getDuration() - Method in class org.encog.ml.schedule.ActionNode
-
- getEarliestStartTime() - Method in class org.encog.ml.schedule.ActionNode
-
- getEGB() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- getElapsedMilliseconds() - Method in class org.encog.util.Stopwatch
-
- getElapsedTicks() - Method in class org.encog.util.Stopwatch
-
- getElementCount() - Method in class org.encog.ca.universe.basic.BasicCellFactory
-
- getElementPos(NEATGenome, long) - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
Get the specified neuron's index.
- getElements() - Method in class org.encog.bot.browse.range.DocumentRange
-
- getEliteRate() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getEncodeLength() - Method in class org.encog.neural.flat.FlatNetwork
-
- getEncogType(String) - Method in class org.encog.persist.EncogDirectoryPersistence
-
Get the type of an Encog object in an EG file, without the
need to read the entire file.
- getEnd() - Method in class org.encog.bot.browse.range.DocumentRange
-
- getEndingIndex() - Method in class org.encog.app.quant.indicators.Indicator
-
- getEndingIndex() - Method in class org.encog.util.normalize.segregate.index.IndexRangeSegregator
-
- getEndingIndex() - Method in class org.encog.util.normalize.segregate.index.IndexSampleSegregator
-
- getEndTraining() - Method in class org.encog.neural.flat.FlatNetwork
-
- getEntries(String, String) - Method in class org.encog.app.analyst.script.prop.PropertyConstraints
-
Get all entries for a section/subsection.
- getEntry(String, String, String) - Method in class org.encog.app.analyst.script.prop.PropertyConstraints
-
Get a single property entry.
- getEntryType() - Method in class org.encog.app.analyst.script.prop.PropertyEntry
-
- getEnumCount(int) - Method in class org.encog.ml.prg.EncogProgramContext
-
Get the enum ordinal count for the specified enumeration type.
- getEnumType() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- getEnumType() - Method in class org.encog.ml.prg.VariableMapping
-
- getEnumValueCount() - Method in class org.encog.ml.prg.VariableMapping
-
- geteOpt() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getEq() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getEq() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getEquilateral() - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
- getError(EnsembleDataSet) - Method in interface org.encog.ensemble.EnsembleML
-
Get the error for this ML on the dataset
- getError(EnsembleDataSet) - Method in class org.encog.ensemble.GenericEnsembleML
-
- getError() - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
- getError() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getError() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getError() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- getError() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- getError() - Method in class org.encog.ml.train.BasicTraining
- getError() - Method in interface org.encog.ml.train.MLTrain
-
- getError() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
- getError() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- getError() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getErrorCalculation() - Method in class org.encog.neural.networks.training.propagation.GradientWorker
-
- getEstimator() - Method in class org.encog.ml.graph.search.AStarSearch
-
- getEvent(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Get an event based on the string label.
- getEvent() - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- getEventError(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Get an event based on label, throw an error if not found.
- getEventIndex(BayesianEvent) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- getEventMap() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- getEvents() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- getEvents() - Method in class org.encog.ml.bayesian.query.BasicQuery
- getEvents() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- getEventState(BayesianEvent) - Method in class org.encog.ml.bayesian.query.BasicQuery
-
Get the event state for a given event.
- getEventState(BayesianEvent) - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
Get the event state for a given event.
- getEventType(BayesianEvent) - Method in class org.encog.ml.bayesian.query.BasicQuery
-
Get the event type.
- getEventType(BayesianEvent) - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
Get the event type.
- getEventType() - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- getEvidenceEvents() - Method in class org.encog.ml.bayesian.query.BasicQuery
- getEvidenceEvents() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- getEvidenceSegements() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getExchange() - Method in class org.encog.ml.data.market.TickerSymbol
-
- getExclude() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getExcluded() - Method in class org.encog.app.analyst.csv.filter.FilterCSV
-
- getExpressionType() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- getExtension() - Method in enum org.encog.app.generate.TargetLanguage
-
- getExtraData(String) - Method in class org.encog.ml.prg.EncogProgram
-
Get extra data that might be needed by user extended opcodes.
- getF1Count() - Method in class org.encog.neural.art.ART1
-
- getF1Count() - Method in class org.encog.neural.bam.BAM
-
- getF2Count() - Method in class org.encog.neural.art.ART1
-
- getF2Count() - Method in class org.encog.neural.bam.BAM
-
- getFactoryArchitecture() - Method in interface org.encog.ml.MLFactory
-
- getFactoryArchitecture() - Method in class org.encog.neural.networks.BasicNetwork
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationBiPolar
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationClippedLinear
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationCompetitive
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationElliott
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationElliottSymmetric
- getFactoryCode() - Method in interface org.encog.engine.network.activation.ActivationFunction
-
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationGaussian
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationLinear
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationLOG
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationRamp
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationSigmoid
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationSIN
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationSoftMax
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationSteepenedSigmoid
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationStep
- getFactoryCode() - Method in class org.encog.engine.network.activation.ActivationTANH
- getFactoryType() - Method in interface org.encog.ml.MLFactory
-
- getFactoryType() - Method in class org.encog.neural.networks.BasicNetwork
- getFalseValue() - Method in class org.encog.util.normalize.output.nominal.OutputOneOf
-
- getFc() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getFetchSize() - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
-
- getField(String, int) - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- getField() - Method in class org.encog.util.normalize.input.MLDataFieldHolder
-
- getField() - Method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
- getFieldNumber() - Method in class org.encog.app.analyst.csv.filter.ExcludedField
-
- getFields() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getFields() - Method in class org.encog.app.analyst.script.process.AnalystProcess
-
The fields.
- getFields() - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
- getFieldValue() - Method in class org.encog.app.analyst.csv.filter.ExcludedField
-
- getFile() - Method in class org.encog.app.analyst.script.segregate.AnalystSegregateTarget
-
- getFile() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- getFile() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getFile() - Method in class org.encog.util.normalize.input.InputFieldCSV
-
- getFileExt(File) - Static method in class org.encog.util.file.FileUtil
-
- getFilename() - Method in class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
-
- getFilename(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a filename.
- getFilename() - Method in class org.encog.ml.data.specific.CSVNeuralDataSet
-
- getFileName(File) - Static method in class org.encog.util.file.FileUtil
-
- getFilenames() - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get all filenames.
- getFileVersion() - Method in class org.encog.ca.universe.basic.PersistBasicUniverse
-
- getFileVersion() - Method in class org.encog.ml.bayesian.PersistBayes
-
- getFileVersion() - Method in class org.encog.ml.hmm.PersistHMM
- getFileVersion() - Method in class org.encog.ml.prg.PersistPrgPopulation
- getFileVersion() - Method in class org.encog.ml.svm.PersistSVM
-
- getFileVersion() - Method in class org.encog.neural.art.PersistART1
- getFileVersion() - Method in class org.encog.neural.bam.PersistBAM
- getFileVersion() - Method in class org.encog.neural.cpn.PersistCPN
- getFileVersion() - Method in class org.encog.neural.neat.PersistNEATPopulation
-
- getFileVersion() - Method in class org.encog.neural.networks.PersistBasicNetwork
- getFileVersion() - Method in class org.encog.neural.networks.training.propagation.PersistTrainingContinuation
- getFileVersion() - Method in class org.encog.neural.pnn.PersistBasicPNN
- getFileVersion() - Method in class org.encog.neural.rbf.PersistRBFNetwork
- getFileVersion() - Method in class org.encog.neural.som.PersistSOM
- getFileVersion() - Method in class org.encog.neural.thermal.PersistBoltzmann
- getFileVersion() - Method in class org.encog.neural.thermal.PersistHopfield
- getFileVersion() - Method in interface org.encog.persist.EncogPersistor
-
- getFilteredRowCount() - Method in class org.encog.app.analyst.csv.filter.FilterCSV
-
- getFinishNode() - Method in class org.encog.ml.schedule.ScheduleGraph
-
- getFlat() - Method in class org.encog.neural.networks.BasicNetwork
- getFlat() - Method in interface org.encog.neural.networks.ContainsFlat
-
- getFlat() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
- getFlat() - Method in class org.encog.neural.rbf.RBFNetwork
- getFold() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getFold() - Method in class org.encog.ml.svm.training.SVMTrain
-
- getFolded() - Method in class org.encog.neural.networks.training.cross.CrossTraining
-
- getFolds() - Method in class org.encog.ml.data.cross.KFoldCrossvalidation
-
- getForDefinition() - Method in class org.encog.ml.bayesian.bif.BIFDefinition
-
- getFormat() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getFormat() - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- getFormat() - Method in class org.encog.ml.data.specific.CSVNeuralDataSet
-
- getFormat() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- getFormat() - Method in class org.encog.ml.prg.EncogProgramContext
-
- getFormat() - Method in class org.encog.util.csv.ReadCSV
-
- getForwardWindowSize() - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- getFrom() - Method in class org.encog.ml.graph.BasicEdge
-
- getFrom() - Method in class org.encog.neural.networks.NeuralDataMapping
-
- getFrom() - Method in class org.encog.util.time.TimeSpan
-
- getFromNeuron() - Method in class org.encog.neural.neat.NEATLink
-
- getFromNeuronID() - Method in class org.encog.neural.neat.training.NEATLinkGene
-
- getFull() - Method in class org.encog.app.quant.util.BarBuffer
-
Determine if the buffer is full.
- getFunctions() - Method in class org.encog.ml.prg.EncogProgram
-
- getFunctions() - Method in class org.encog.ml.prg.EncogProgramContext
-
- getGamma() - Method in class org.encog.ml.svm.training.SVMTrain
-
- getGammaBegin() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getGammaEnd() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getGammaStep() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- getGeneIDGenerate() - Method in class org.encog.neural.neat.NEATPopulation
-
- getGenerator() - Method in class org.encog.ml.prg.opp.SubtreeMutation
-
- getGenetic() - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
- getGenomeFactory() - Method in class org.encog.ml.ea.population.BasicPopulation
- getGenomeFactory() - Method in interface org.encog.ml.ea.population.Population
-
- getGenomeFactory() - Method in class org.encog.neural.neat.NEATPopulation
- getGensNoImprovement() - Method in class org.encog.ml.ea.species.BasicSpecies
- getGensNoImprovement() - Method in interface org.encog.ml.ea.species.Species
-
- getGivenDefinitions() - Method in class org.encog.ml.bayesian.bif.BIFDefinition
-
- getGivenEvents() - Method in class org.encog.ml.bayesian.parse.ParsedProbability
-
- getGl() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getGoal() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getGoal() - Method in class org.encog.ml.graph.search.AbstractGraphSearch
-
- getGoal() - Method in interface org.encog.ml.graph.search.GraphSearch
-
- getGoal() - Method in class org.encog.ml.world.learning.mdp.MarkovDecisionProcess
-
- getGoalDestination() - Method in class org.encog.ml.graph.search.SimpleDestinationGoal
-
- getGoals() - Method in class org.encog.ml.world.basic.BasicWorld
-
- getGoals() - Method in interface org.encog.ml.world.World
-
- getGradients() - Method in class org.encog.mathutil.matrices.hessian.BasicHessian
-
The gradeints.
- getGradients() - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
- getGradients() - Method in interface org.encog.mathutil.matrices.hessian.ComputeHessian
-
The gradeints.
- getGraph() - Method in class org.encog.ml.graph.search.AbstractGraphSearch
-
- getGraph() - Method in interface org.encog.ml.graph.search.GraphSearch
-
- getGroup() - Method in class org.encog.util.normalize.output.OutputFieldGrouped
-
- getGroupedFields() - Method in class org.encog.util.normalize.output.BasicOutputFieldGroup
-
- getGroupedFields() - Method in interface org.encog.util.normalize.output.OutputFieldGroup
-
- getGroups() - Method in class org.encog.util.normalize.DataNormalization
-
- getH() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition
-
Return the Householder vectors
- getHasContext() - Method in class org.encog.neural.flat.FlatNetwork
-
- getHeader(int) - Method in class org.encog.app.analyst.util.CSVHeaders
-
Get the specified header.
- getHeaderBuffer() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getHeaders() - Method in class org.encog.app.analyst.util.CSVHeaders
-
- getHeadingMap() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getHeight() - Method in class org.encog.platformspecific.j2se.data.image.ImageMLDataSet
-
- getHeight() - Method in class org.encog.util.ImageSize
-
- getHessian() - Method in class org.encog.mathutil.matrices.hessian.BasicHessian
- getHessian() - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
- getHessian() - Method in interface org.encog.mathutil.matrices.hessian.ComputeHessian
-
- getHessian() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
- getHessianMatrix() - Method in class org.encog.mathutil.matrices.hessian.BasicHessian
- getHessianMatrix() - Method in interface org.encog.mathutil.matrices.hessian.ComputeHessian
-
- getHidden() - Method in class org.encog.neural.prune.PruneIncremental
-
- getHidden1Size() - Method in class org.encog.neural.prune.PruneIncremental
-
- getHidden2Size() - Method in class org.encog.neural.prune.PruneIncremental
-
- getHiddenNodes() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getHigh() - Method in class org.encog.engine.network.activation.ActivationRamp
-
- getHigh() - Method in class org.encog.engine.network.activation.ActivationStep
-
- getHigh() - Method in class org.encog.mathutil.IntRange
-
- getHigh() - Method in class org.encog.mathutil.NumericRange
-
- getHigh() - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- getHigh() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getHigh() - Method in class org.encog.neural.prune.PruneIncremental
-
- getHigh() - Method in class org.encog.util.normalize.output.mapped.MappedRange
-
- getHigh() - Method in class org.encog.util.normalize.output.nominal.NominalItem
-
- getHigh() - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
- getHigh() - Method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
- getHigh() - Method in class org.encog.util.normalize.segregate.SegregationRange
-
- getHighSequence() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getId() - Method in class org.encog.neural.hyperneat.substrate.SubstrateNode
-
- getId() - Method in class org.encog.neural.neat.training.NEATBaseGene
-
- getID() - Method in class org.encog.util.concurrency.TaskGroup
-
- getIdAttribute() - Method in class org.encog.bot.browse.range.DocumentRange
-
- getIdeal() - Method in class org.encog.ml.data.basic.BasicMLDataPair
- getIdeal() - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
- getIdeal() - Method in interface org.encog.ml.data.MLDataPair
-
- getIdealArray() - Method in class org.encog.ml.data.basic.BasicMLDataPair
- getIdealArray() - Method in interface org.encog.ml.data.MLDataPair
-
- getIdealCount() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getIdealSize() - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- getIdealSize() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- getIdealSize() - Method in class org.encog.ml.data.basic.BasicMLDataSet
- getIdealSize() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
- getIdealSize() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- getIdealSize() - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
- getIdealSize() - Method in class org.encog.ml.data.buffer.codec.CSVDataCODEC
- getIdealSize() - Method in interface org.encog.ml.data.buffer.codec.DataSetCODEC
-
- getIdealSize() - Method in class org.encog.ml.data.buffer.codec.ExcelCODEC
- getIdealSize() - Method in class org.encog.ml.data.buffer.codec.NeuralDataSetCODEC
- getIdealSize() - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
- getIdealSize() - Method in class org.encog.ml.data.folded.FoldedDataSet
- getIdealSize() - Method in interface org.encog.ml.data.MLDataSet
-
- getIdealSize() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
- getImage() - Method in class org.encog.platformspecific.j2se.data.image.ImageMLData
-
- getImageHeight() - Method in interface org.encog.util.downsample.Downsample
-
- getImageHeight() - Method in class org.encog.util.downsample.RGBDownsample
-
- getImagEigenvalues() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition
-
Return the imaginary parts of the eigenvalues.
- getImageWidth() - Method in interface org.encog.util.downsample.Downsample
-
- getImageWidth() - Method in class org.encog.util.downsample.RGBDownsample
-
- getImaginary() - Method in class org.encog.mathutil.ComplexNumber
-
Imaginary part of this Complex number
(the y-coordinate in rectangular coordinates).
- getImplementationType() - Method in class org.encog.ml.ea.train.basic.TrainEA
- getImplementationType() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- getImplementationType() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- getImplementationType() - Method in class org.encog.ml.train.BasicTraining
-
- getImplementationType() - Method in interface org.encog.ml.train.MLTrain
-
- getImplementationType() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
- getIncludes() - Method in class org.encog.app.generate.generators.AbstractGenerator
-
- getIncrement() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
- getIndentLevel() - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
- getIndex() - Method in class org.encog.app.analyst.csv.basic.FileData
-
- getIndex() - Method in class org.encog.app.analyst.csv.sort.SortedField
-
- getIndex() - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- getIndex() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getIndex() - Method in class org.encog.util.arrayutil.ClassItem
-
- getInertiaWeight() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Get the inertia weight (w)
- getInitialConnectionDensity() - Method in class org.encog.neural.neat.NEATPopulation
-
- getInitialUpdate() - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
-
- getInitNetwork() - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
- getInnovationId() - Method in class org.encog.neural.neat.training.NEATBaseGene
-
- getInnovationID() - Method in class org.encog.neural.neat.training.NEATInnovation
-
- getInnovationIDGenerate() - Method in class org.encog.neural.neat.NEATPopulation
-
- getInnovations() - Method in class org.encog.neural.neat.NEATPopulation
-
- getInnovations() - Method in class org.encog.neural.neat.training.NEATInnovationList
-
- getInput() - Method in class org.encog.ml.data.basic.BasicMLDataPair
- getInput() - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
- getInput() - Method in interface org.encog.ml.data.MLDataPair
-
- getInput() - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- getInputArray() - Method in class org.encog.ml.data.basic.BasicMLDataPair
- getInputArray() - Method in interface org.encog.ml.data.MLDataPair
-
- getInputColumns() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- getInputCount() - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- getInputCount() - Method in class org.encog.ensemble.GenericEnsembleML
-
- getInputCount() - Method in class org.encog.ml.bayesian.BayesianNetwork
- getInputCount() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getInputCount() - Method in class org.encog.ml.fitting.gaussian.GaussianFitting
-
- getInputCount() - Method in class org.encog.ml.fitting.linear.LinearRegression
-
- getInputCount() - Method in interface org.encog.ml.MLInput
-
- getInputCount() - Method in class org.encog.ml.prg.EncogProgram
- getInputCount() - Method in class org.encog.ml.prg.train.PrgPopulation
- getInputCount() - Method in class org.encog.ml.svm.SVM
-
- getInputCount() - Method in class org.encog.neural.art.ART1
-
- getInputCount() - Method in class org.encog.neural.cpn.CPN
- getInputCount() - Method in class org.encog.neural.flat.FlatNetwork
-
- getInputCount() - Method in class org.encog.neural.freeform.FreeformNetwork
- getInputCount() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getInputCount() - Method in class org.encog.neural.neat.NEATNetwork
- getInputCount() - Method in class org.encog.neural.neat.NEATPopulation
- getInputCount() - Method in class org.encog.neural.neat.training.NEATGenome
-
- getInputCount() - Method in class org.encog.neural.networks.BasicNetwork
- getInputCount() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getInputCount() - Method in class org.encog.neural.rbf.RBFNetwork
- getInputCount() - Method in class org.encog.neural.som.SOM
- getInputCount() - Method in class org.encog.neural.thermal.BoltzmannMachine
- getInputCount() - Method in class org.encog.neural.thermal.HopfieldNetwork
- getInputData() - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- getInputFeatures() - Method in class org.encog.ml.model.EncogModel
-
- getInputField() - Method in class org.encog.util.normalize.output.nominal.NominalItem
-
- getInputFields() - Method in class org.encog.util.normalize.DataNormalization
-
- getInputFilename() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getInputHeadings() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getInputNeuronCount() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getInputNeuronCount() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
- getInputNeurons() - Method in class org.encog.neural.pattern.PNNPattern
-
- getInputNeurons() - Method in class org.encog.neural.pattern.SVMPattern
-
- getInputNodes() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getInputNormalizers() - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
- getInputSize() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getInputSize() - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- getInputSize() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- getInputSize() - Method in class org.encog.ml.data.basic.BasicMLDataSet
- getInputSize() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
- getInputSize() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- getInputSize() - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
- getInputSize() - Method in class org.encog.ml.data.buffer.codec.CSVDataCODEC
- getInputSize() - Method in interface org.encog.ml.data.buffer.codec.DataSetCODEC
-
- getInputSize() - Method in class org.encog.ml.data.buffer.codec.ExcelCODEC
- getInputSize() - Method in class org.encog.ml.data.buffer.codec.NeuralDataSetCODEC
- getInputSize() - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
- getInputSize() - Method in class org.encog.ml.data.folded.FoldedDataSet
- getInputSize() - Method in interface org.encog.ml.data.MLDataSet
-
- getInputSize() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
- getInputSummation() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
- getInputSummation() - Method in interface org.encog.neural.freeform.FreeformNeuron
-
- getInputWindow() - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
- getInputWindowSize() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getInstance() - Static method in class org.encog.app.analyst.script.prop.PropertyConstraints
-
- getInstance() - Static method in class org.encog.Encog
-
Get the instance to the singleton.
- getInstance() - Static method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
- getInstance() - Static method in class org.encog.persist.PersistorRegistry
-
- getInstance() - Static method in class org.encog.util.concurrency.EngineConcurrency
-
- getInstarCount() - Method in class org.encog.neural.cpn.CPN
-
- getInt(int) - Method in class org.encog.util.csv.ReadCSV
-
Obtain a column as an integer referenced by a string.
- getInt(String, boolean, int) - Method in class org.encog.util.ParamsHolder
-
Get a param as a integer.
- getItems() - Method in class org.encog.bot.rss.RSS
-
- getItems() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getIteration() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getIteration() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getIteration() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- getIteration() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- getIteration() - Method in class org.encog.ml.train.BasicTraining
-
- getIteration() - Method in interface org.encog.ml.train.MLTrain
-
- getIteration() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
- getIterations() - Method in class org.encog.neural.prune.PruneIncremental
-
- getIterator() - Method in class org.encog.util.normalize.input.MLDataFieldHolder
-
- getJobUnit() - Method in class org.encog.util.concurrency.job.JobUnitContext
-
- getK() - Method in class org.encog.ml.data.cross.KFoldCrossvalidation
-
- getK() - Method in class org.encog.util.text.BagOfWords
-
- getKernel() - Method in class org.encog.neural.pattern.PNNPattern
-
- getKernel() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getKernelType() - Method in class org.encog.ml.svm.SVM
-
- getKey() - Method in class org.encog.app.analyst.script.prop.PropertyEntry
-
- getKfold() - Method in class org.encog.app.analyst.commands.Cmd
-
- getL() - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition
-
Return triangular factor.
- getL() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Return lower triangular factor
- getL() - Method in class org.encog.neural.art.ART1
-
- getL() - Method in class org.encog.neural.pattern.ART1Pattern
-
- getLabel() - Method in class org.encog.ensemble.aggregator.Averaging
-
- getLabel() - Method in class org.encog.ensemble.aggregator.MajorityVoting
-
- getLabel() - Method in class org.encog.ensemble.aggregator.MetaClassifier
-
- getLabel() - Method in interface org.encog.ensemble.EnsembleAggregator
-
- getLabel() - Method in interface org.encog.ensemble.EnsembleML
-
- getLabel() - Method in interface org.encog.ensemble.EnsembleMLMethodFactory
-
- getLabel() - Method in interface org.encog.ensemble.EnsembleTrainFactory
-
- getLabel() - Method in class org.encog.ensemble.GenericEnsembleML
-
- getLabel() - Method in class org.encog.ensemble.ml.mlp.factory.MultiLayerPerceptronFactory
-
- getLabel() - Method in class org.encog.ensemble.training.BackpropagationFactory
-
- getLabel() - Method in class org.encog.ensemble.training.LevenbergMarquardtFactory
-
- getLabel() - Method in class org.encog.ensemble.training.ManhattanPropagationFactory
-
- getLabel() - Method in class org.encog.ensemble.training.ResilientPropagationFactory
-
- getLabel() - Method in class org.encog.ensemble.training.ScaledConjugateGradientFactory
-
- getLabel() - Method in class org.encog.mathutil.probability.vars.RandomVariable
-
- getLabel() - Method in class org.encog.ml.bayesian.BayesianChoice
-
- getLabel() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- getLabel() - Method in class org.encog.ml.bayesian.parse.ParsedChoice
-
- getLabel() - Method in class org.encog.ml.bayesian.parse.ParsedEvent
-
- getLabel() - Method in class org.encog.ml.graph.BasicNode
-
- getLabel() - Method in interface org.encog.ml.world.Action
-
- getLabel() - Method in class org.encog.ml.world.basic.BasicAction
-
- getLagDepth() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getLagDepth() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getLagWindowSize() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getLagWindowSize() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- getLaplaceClasses() - Method in class org.encog.util.text.BagOfWords
-
- getLargeArrays() - Method in class org.encog.persist.EncogFileSection
-
- getLast() - Method in class org.encog.util.arrayutil.WindowDouble
-
Get the last value from the window.
- getLastDelta() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
- getLastDelta() - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
- getLastGradient() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
- getLastValue() - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- getLatestStartTime() - Method in class org.encog.ml.schedule.ActionNode
-
- getLayerBiasActivation(int) - Method in class org.encog.neural.networks.BasicNetwork
-
Get the bias activation for the specified layer.
- getLayerContextCount() - Method in class org.encog.neural.flat.FlatNetwork
-
- getLayerCount() - Method in class org.encog.neural.networks.BasicNetwork
-
- getLayerCounts() - Method in class org.encog.neural.flat.FlatNetwork
-
- getLayerFeedCounts() - Method in class org.encog.neural.flat.FlatNetwork
-
- getLayerIndex() - Method in class org.encog.neural.flat.FlatNetwork
-
- getLayerNeuronCount(int) - Method in class org.encog.neural.networks.BasicNetwork
-
Get the neuron count.
- getLayerOutput() - Method in class org.encog.neural.flat.FlatNetwork
-
- getLayerOutput(int, int) - Method in class org.encog.neural.networks.BasicNetwork
-
Get the layer output for the specified neuron.
- getLayers() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
- getLayerSums() - Method in class org.encog.neural.flat.FlatNetwork
-
- getLayerTotalNeuronCount(int) - Method in class org.encog.neural.networks.BasicNetwork
-
Get the total (including bias and context) neuron cont for a layer.
- getLeadDepth() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getLeadDepth() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getLeader() - Method in class org.encog.ml.ea.species.BasicSpecies
- getLeader() - Method in interface org.encog.ml.ea.species.Species
-
- getLeadWindowSize() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getLeadWindowSize() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- getLearningRate() - Method in class org.encog.ensemble.training.ManhattanPropagationFactory
-
- getLearningRate() - Method in class org.encog.neural.cpn.training.TrainInstar
- getLearningRate() - Method in class org.encog.neural.cpn.training.TrainOutstar
- getLearningRate() - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
-
- getLearningRate() - Method in interface org.encog.neural.networks.training.LearningRate
-
- getLearningRate() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
- getLearningRate() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
- getLearningRate() - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
- getLearningRate() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
- getLearningRate() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
- getLen() - Method in class org.encog.ml.hmm.alog.KullbackLeiblerDistanceCalculator
-
- getLength() - Method in class org.encog.util.normalize.output.multiplicative.MultiplicativeGroup
-
- getLength() - Method in class org.encog.util.normalize.output.zaxis.ZAxisGroup
-
- getLimit() - Method in class org.encog.ca.program.generic.Trans
-
- getLine() - Method in class org.encog.util.SimpleParser
-
- getLines() - Method in class org.encog.app.analyst.script.task.AnalystTask
-
- getLines() - Method in class org.encog.ml.bayesian.table.BayesianTable
-
- getLines() - Method in class org.encog.persist.EncogFileSection
-
- getLinesAsString() - Method in class org.encog.persist.EncogFileSection
-
- getLink() - Method in class org.encog.bot.rss.RSSItem
-
Get the hyperlink.
- getLinkCount() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getLinks() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getLinks() - Method in class org.encog.neural.neat.NEATNetwork
-
- getLinksChromosome() - Method in class org.encog.neural.neat.training.NEATGenome
-
- getLinkSelection() - Method in class org.encog.neural.neat.training.opp.NEATMutateWeights
-
- getList() - Method in class org.encog.ml.bayesian.parse.ParsedEvent
-
- getList() - Method in class org.encog.util.obj.ChooseObject
-
- getListeners() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getLoader() - Method in class org.encog.ml.data.market.MarketMLDataSet
-
- getLocation() - Method in class org.encog.neural.hyperneat.substrate.SubstrateNode
-
- getLoggingPlugin() - Method in class org.encog.Encog
-
- getLogLevel() - Method in interface org.encog.plugin.EncogPluginLogging1
-
- getLogLevel() - Method in class org.encog.plugin.system.SystemLoggingPlugin
- getLow() - Method in class org.encog.engine.network.activation.ActivationRamp
-
- getLow() - Method in class org.encog.engine.network.activation.ActivationStep
-
- getLow() - Method in class org.encog.mathutil.IntRange
-
- getLow() - Method in class org.encog.mathutil.NumericRange
-
- getLow() - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- getLow() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getLow() - Method in class org.encog.neural.prune.PruneIncremental
-
- getLow() - Method in class org.encog.util.normalize.output.mapped.MappedRange
-
- getLow() - Method in class org.encog.util.normalize.output.nominal.NominalItem
-
- getLow() - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
- getLow() - Method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
- getLow() - Method in class org.encog.util.normalize.segregate.SegregationRange
-
- getLower() - Method in class org.encog.mathutil.dimension.DimensionConstraint
-
- getLower(int) - Method in class org.encog.mathutil.dimension.DimensionConstraint
-
Get the lower bound for a specific dimension.
- getLowSequence() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getManager() - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer
-
Get the manager.
- getManager() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
-
Get the manager.
- getMap() - Method in class org.encog.util.http.CookieUtility
-
Allows access to the name/value pair list of cookies.
- getMappings() - Method in class org.encog.util.normalize.input.InputFieldCSVText
-
- getMask() - Method in class org.encog.ml.data.versatile.division.DataDivision
-
- getMask() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- getMatrix(int, int, int, int) - Method in class org.encog.mathutil.matrices.Matrix
-
Get a submatrix.
- getMatrix(int, int, int[]) - Method in class org.encog.mathutil.matrices.Matrix
-
Get a submatrix.
- getMatrix(int[], int, int) - Method in class org.encog.mathutil.matrices.Matrix
-
Get a submatrix.
- getMatrix(int[], int[]) - Method in class org.encog.mathutil.matrices.Matrix
-
Get a submatrix.
- getMax() - Method in class org.encog.app.analyst.script.DataField
-
- getMax() - Method in class org.encog.ca.universe.basic.BasicCellFactory
-
- getMax() - Method in class org.encog.mathutil.randomize.RangeRandomizer
-
- getMax() - Method in class org.encog.ml.bayesian.BayesianChoice
-
- getMax() - Method in class org.encog.ml.bayesian.parse.ParsedChoice
-
- getMax() - Method in class org.encog.neural.prune.HiddenLayerParams
-
- getMax() - Method in class org.encog.util.normalize.input.BasicInputField
-
- getMax() - Method in interface org.encog.util.normalize.input.InputField
-
- getMaxConst() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getMaxDepth() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getMaxEnumType() - Method in class org.encog.ml.prg.EncogProgramContext
-
Get the max enum type for all defined variables.
- getMaxError() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getMaxError() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- getMaxGenerationErrors() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getMaxGenerationErrors() - Method in interface org.encog.ml.prg.generator.PrgGenerator
-
- getMaximumParents() - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
- getMaxIndividualSize() - Method in class org.encog.ml.ea.population.BasicPopulation
- getMaxIndividualSize() - Method in interface org.encog.ml.ea.population.Population
-
- getMaxIndividualSize() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getMaxIndividualSize() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getMaxIteration() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getMaxLines() - Method in class org.encog.ml.bayesian.table.BayesianTable
-
- getMaxNumberOfSpecies() - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- getMaxOperationErrors() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getMaxPosition() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Get the boundary of the search space (Xmax)
- getMaxStep() - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
-
- getMaxTries() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getMaxTries() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getMaxVelocity() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Get the maximum velocity (Vmax)
- getMaxWeight() - Method in class org.encog.neural.hyperneat.HyperNEATCODEC
-
- getMaxWinners() - Method in class org.encog.engine.network.activation.ActivationCompetitive
-
- getMean() - Method in class org.encog.app.analyst.script.DataField
-
- getMean() - Method in class org.encog.mathutil.NumericRange
-
- getMean() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getMean() - Method in class org.encog.ml.hmm.distributions.ContinousDistribution
-
- getMember(int) - Method in class org.encog.ensemble.bagging.Bagging
-
- getMember(int) - Method in class org.encog.ensemble.Ensemble
-
Extract a specific MLMethod
- getMember(int) - Method in class org.encog.ensemble.stacking.Stacking
-
- getMembers() - Method in class org.encog.ml.ea.species.BasicSpecies
- getMembers() - Method in interface org.encog.ml.ea.species.Species
-
- getMemoryScore() - Method in class org.encog.util.benchmark.EncogBenchmark
-
- getMethod() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getMethod() - Method in class org.encog.bot.browse.range.Form
-
- getMethod() - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.ml.data.cross.DataFold
-
- getMethod() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
- getMethod() - Method in class org.encog.ml.fitting.gaussian.TrainGaussian
-
- getMethod() - Method in class org.encog.ml.fitting.linear.TrainLinearRegression
-
- getMethod() - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- getMethod() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- getMethod() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.ml.svm.training.SVMTrain
-
Get the current best machine learning method from the training.
- getMethod() - Method in interface org.encog.ml.train.MLTrain
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.cpn.training.TrainInstar
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.cpn.training.TrainOutstar
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.networks.training.cross.CrossTraining
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
- getMethod() - Method in class org.encog.neural.networks.training.nm.NelderMeadTraining
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
- getMethod() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.rbf.training.SVDTraining
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Get the current best machine learning method from the training.
- getMethod() - Method in class org.encog.neural.som.training.clustercopy.SOMClusterCopyTraining
-
Get the current best machine learning method from the training.
- getMethodConfigurations() - Method in class org.encog.ml.model.EncogModel
-
- getMethodName() - Method in class org.encog.ml.model.config.FeedforwardConfig
- getMethodName() - Method in interface org.encog.ml.model.config.MethodConfig
-
- getMethodName() - Method in class org.encog.ml.model.config.NEATConfig
- getMethodName() - Method in class org.encog.ml.model.config.PNNConfig
- getMethodName() - Method in class org.encog.ml.model.config.RBFNetworkConfig
- getMethodName() - Method in class org.encog.ml.model.config.SVMConfig
- getMethodType() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getMiddle(int) - Method in class org.encog.mathutil.dimension.DimensionConstraint
-
- getMin() - Method in class org.encog.app.analyst.script.DataField
-
- getMin() - Method in class org.encog.ca.universe.basic.BasicCellFactory
-
- getMin() - Method in class org.encog.mathutil.randomize.RangeRandomizer
-
- getMin() - Method in class org.encog.ml.bayesian.BayesianChoice
-
- getMin() - Method in class org.encog.ml.bayesian.parse.ParsedChoice
-
- getMin() - Method in class org.encog.neural.prune.HiddenLayerParams
-
- getMin() - Method in class org.encog.util.normalize.input.BasicInputField
-
- getMin() - Method in interface org.encog.util.normalize.input.InputField
-
- getMinClassCount() - Method in class org.encog.app.analyst.script.DataField
-
Determine the minimum class count.
- getMinConst() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getMinDepth() - Method in class org.encog.ml.prg.generator.RampedHalfAndHalf
-
- getMinEfficiency() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getMinImprovement() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- getMinutePeriod(int, int) - Static method in class org.encog.util.time.NumericDateUtil
-
- getMinutes() - Method in class org.encog.ml.train.strategy.end.EndMinutesStrategy
-
- getMinutesLeft() - Method in class org.encog.ml.train.strategy.end.EndMinutesStrategy
-
- getMinWeight() - Method in class org.encog.neural.hyperneat.HyperNEATCODEC
-
- getMissing() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getMissingValues() - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
-
- getMl() - Method in interface org.encog.ensemble.EnsembleML
-
- getMl() - Method in class org.encog.ensemble.GenericEnsembleML
-
- getMode() - Static method in class org.encog.mathutil.error.ErrorCalculation
-
get the error calculation mode, this is static and therefore global to
all Enocg training.
- getModel() - Method in class org.encog.ml.svm.SVM
-
- getModulus() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
- getMomentum() - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
-
- getMomentum() - Method in interface org.encog.neural.networks.training.Momentum
-
- getMomentum() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
- getMonth(long) - Static method in class org.encog.util.time.NumericDateUtil
-
- getMovements() - Method in class org.encog.ca.program.basic.BasicProgram
-
- getMu() - Method in class org.encog.ml.fitting.gaussian.GaussianFitting
-
- getMult() - Method in class org.encog.ca.program.generic.Trans
-
- getMultiplier() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
- getMultiplier() - Method in class org.encog.util.normalize.output.zaxis.ZAxisGroup
-
- getName() - Method in class org.encog.app.analyst.commands.Cmd
-
- getName() - Method in class org.encog.app.analyst.commands.CmdBalance
- getName() - Method in class org.encog.app.analyst.commands.CmdCluster
- getName() - Method in class org.encog.app.analyst.commands.CmdCode
- getName() - Method in class org.encog.app.analyst.commands.CmdCreate
- getName() - Method in class org.encog.app.analyst.commands.CmdEvaluate
- getName() - Method in class org.encog.app.analyst.commands.CmdEvaluateRaw
- getName() - Method in class org.encog.app.analyst.commands.CmdGenerate
- getName() - Method in class org.encog.app.analyst.commands.CmdNormalize
- getName() - Method in class org.encog.app.analyst.commands.CmdProcess
- getName() - Method in class org.encog.app.analyst.commands.CmdRandomize
- getName() - Method in class org.encog.app.analyst.commands.CmdReset
- getName() - Method in class org.encog.app.analyst.commands.CmdSegregate
- getName() - Method in class org.encog.app.analyst.commands.CmdSet
- getName() - Method in class org.encog.app.analyst.commands.CmdTrain
- getName() - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
- getName() - Method in class org.encog.app.analyst.script.AnalystClassItem
-
- getName() - Method in class org.encog.app.analyst.script.DataField
-
- getName() - Method in class org.encog.app.analyst.script.ml.ScriptOpcode
-
- getName() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getName() - Method in class org.encog.app.analyst.script.preprocess.FieldPreprocess
-
- getName() - Method in class org.encog.app.analyst.script.process.ProcessField
-
- getName() - Method in class org.encog.app.analyst.script.prop.PropertyEntry
-
- getName() - Method in class org.encog.app.analyst.script.task.AnalystTask
-
- getName() - Method in class org.encog.app.analyst.wizard.SourceElement
-
- getName() - Method in class org.encog.app.generate.program.EncogProgramNode
-
- getName() - Method in class org.encog.bot.browse.range.FormElement
-
- getName() - Method in class org.encog.ml.bayesian.bif.BIFVariable
-
- getName() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getName() - Method in class org.encog.ml.ea.population.BasicPopulation
-
- getName() - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- getName() - Method in class org.encog.ml.prg.extension.BasicTemplate
- getName() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- getName() - Method in class org.encog.ml.prg.ProgramNode
-
- getName() - Method in class org.encog.ml.prg.VariableMapping
-
- getName() - Method in class org.encog.parse.tags.Tag
-
- getName() - Method in class org.encog.util.arrayutil.ClassItem
-
- getName() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getName() - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- getNeighborhood() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
- getNetwork() - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
- getNetwork() - Method in class org.encog.ml.bayesian.bif.BIFHandler
-
- getNetwork() - Method in class org.encog.ml.bayesian.query.BasicQuery
- getNetwork() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- getNetwork() - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
- getNetwork() - Method in class org.encog.neural.networks.layers.BasicLayer
-
- getNetwork() - Method in interface org.encog.neural.networks.layers.Layer
-
- getNetwork() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
- getNetwork() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- getNetwork() - Method in class org.encog.neural.networks.training.propagation.GradientWorker
-
- getNetwork() - Method in class org.encog.neural.prune.PruneSelective
-
- getNetworkDepth() - Method in class org.encog.neural.neat.training.NEATGenome
-
- getNetworkInputLayerSize() - Method in class org.encog.util.normalize.DataNormalization
-
- getNetworkOutputLayerSize() - Method in class org.encog.util.normalize.DataNormalization
-
- getNetworkState(int) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Returns the state of a network in the swarm
- getNeuralDataSet() - Method in class org.encog.util.normalize.input.InputFieldMLDataSet
-
- getNeuronCount() - Method in class org.encog.neural.flat.FlatNetwork
-
- getNeuronCount() - Method in class org.encog.neural.networks.layers.BasicLayer
-
- getNeuronCount() - Method in interface org.encog.neural.networks.layers.Layer
-
- getNeuronCount() - Method in class org.encog.neural.thermal.ThermalNetwork
-
- getNeuronID() - Method in class org.encog.neural.neat.training.NEATInnovation
-
- getNeurons() - Method in class org.encog.neural.freeform.basic.BasicFreeformLayer
- getNeurons() - Method in interface org.encog.neural.freeform.FreeformLayer
-
- getNeuronsChromosome() - Method in class org.encog.neural.neat.training.NEATGenome
-
- getNeuronType() - Method in class org.encog.neural.neat.training.NEATNeuronGene
-
- getNewDataSet() - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- getNewDataSet() - Method in class org.encog.ensemble.data.factories.ResamplingDataSetFactory
-
- getNewDataSet() - Method in class org.encog.ensemble.data.factories.WeightedResamplingDataSetFactory
-
- getNewDataSet() - Method in class org.encog.ensemble.data.factories.WrappingNonResamplingDataSetFactory
-
- getNodeCount() - Method in class org.encog.ml.tree.traverse.tasks.TaskCountNodes
-
- getNodeCount() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getNodeFound() - Method in class org.encog.ml.prg.opp.LevelHolder
-
- getNodes() - Method in class org.encog.ml.graph.BasicGraph
-
- getNodes() - Method in class org.encog.ml.graph.BasicPath
-
- getNodeType() - Method in class org.encog.ml.prg.extension.BasicTemplate
- getNodeType() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- getNormalization() - Method in class org.encog.util.normalize.segregate.index.IndexSegregator
-
- getNormalization() - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
- getNormalization() - Method in class org.encog.util.normalize.segregate.RangeSegregator
-
- getNormalization() - Method in interface org.encog.util.normalize.segregate.Segregator
-
- getNormalize() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getNormalized(int, float, float) - Method in class org.encog.ml.data.auto.AutoFloatColumn
-
- getNormalizedFields() - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
-
- getNormalizedHigh() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getNormalizedHigh() - Method in class org.encog.util.arrayutil.NormalizeArray
-
- getNormalizedHigh() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getNormalizedLow() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getNormalizedLow() - Method in class org.encog.util.arrayutil.NormalizeArray
-
- getNormalizedLow() - Method in class org.encog.util.arrayutil.NormalizedField
-
- getNormalizedMax() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- getNormalizedMin() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- getNormHelper() - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
- getNormStrategy() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- getNoTasks() - Method in class org.encog.util.concurrency.TaskGroup
-
- getNoWinner() - Method in class org.encog.neural.art.ART1
-
- getNullArray() - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
- getNullArray() - Method in class org.encog.app.generate.generators.mql4.GenerateMQL4
-
- getNullArray() - Method in class org.encog.app.generate.generators.ninja.GenerateNinjaScript
-
- getNumber() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
-
- getNumberFormatter() - Method in class org.encog.util.csv.CSVFormat
-
- getNumberOfRecords() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getNumberRemaining() - Method in class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
-
- getNumFolds() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- getNumGenes() - Method in class org.encog.neural.neat.training.NEATGenome
-
- getNumGensAllowedNoImprovement() - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- getNumSigmas() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- getObj() - Method in class org.encog.util.obj.ObjectHolder
-
- getOffset() - Method in class org.encog.util.normalize.input.InputFieldCSV
-
- getOffset() - Method in class org.encog.util.normalize.input.InputFieldEncogCollection
-
- getOffset() - Method in class org.encog.util.normalize.input.InputFieldMLDataSet
-
- getOffspringCount() - Method in class org.encog.ml.ea.species.BasicSpecies
- getOffspringCount() - Method in interface org.encog.ml.ea.species.Species
-
- getOffspringShare() - Method in class org.encog.ml.ea.species.BasicSpecies
- getOffspringShare() - Method in interface org.encog.ml.ea.species.Species
-
- getOldBestGenome() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getOpCode(int) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Get the specified opcode.
- getOpcodes() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getOpCodes() - Method in class org.encog.ml.prg.extension.FunctionFactory
-
- getOperators() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getOperators() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getOptions() - Method in class org.encog.ml.bayesian.bif.BIFVariable
-
- getOriginal() - Method in class org.encog.bot.browse.Address
-
- getOutcomeEvents() - Method in class org.encog.ml.bayesian.query.BasicQuery
- getOutcomeEvents() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- getOutmodel() - Method in class org.encog.neural.pattern.PNNPattern
-
- getOutput() - Method in class org.encog.neural.networks.training.cross.NetworkFold
-
- getOutputColumns() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- getOutputCount() - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- getOutputCount() - Method in class org.encog.ensemble.GenericEnsembleML
-
- getOutputCount() - Method in class org.encog.ml.bayesian.BayesianNetwork
- getOutputCount() - Method in class org.encog.ml.fitting.gaussian.GaussianFitting
-
- getOutputCount() - Method in class org.encog.ml.fitting.linear.LinearRegression
-
- getOutputCount() - Method in interface org.encog.ml.MLOutput
-
- getOutputCount() - Method in class org.encog.ml.prg.EncogProgram
- getOutputCount() - Method in class org.encog.ml.prg.train.PrgPopulation
- getOutputCount() - Method in class org.encog.ml.svm.SVM
-
- getOutputCount() - Method in class org.encog.neural.art.ART1
-
- getOutputCount() - Method in class org.encog.neural.cpn.CPN
- getOutputCount() - Method in class org.encog.neural.flat.FlatNetwork
-
- getOutputCount() - Method in class org.encog.neural.freeform.FreeformNetwork
- getOutputCount() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getOutputCount() - Method in class org.encog.neural.neat.NEATNetwork
- getOutputCount() - Method in class org.encog.neural.neat.NEATPopulation
- getOutputCount() - Method in class org.encog.neural.neat.training.NEATGenome
-
- getOutputCount() - Method in class org.encog.neural.networks.BasicNetwork
- getOutputCount() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getOutputCount() - Method in class org.encog.neural.rbf.RBFNetwork
- getOutputCount() - Method in class org.encog.neural.som.SOM
- getOutputCount() - Method in class org.encog.neural.thermal.BoltzmannMachine
- getOutputCount() - Method in class org.encog.neural.thermal.HopfieldNetwork
- getOutputEpsilon() - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
- getOutputFieldCount() - Method in class org.encog.util.normalize.DataNormalization
-
- getOutputFields() - Method in class org.encog.util.normalize.DataNormalization
-
- getOutputIndex() - Method in class org.encog.neural.neat.NEATNetwork
-
- getOutputLayer() - Method in class org.encog.neural.freeform.FreeformNetwork
-
- getOutputMode() - Method in class org.encog.neural.pnn.AbstractPNN
-
- getOutputNeuron() - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
- getOutputNeuronCount() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getOutputNeuronCount() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
- getOutputNeurons() - Method in class org.encog.neural.pattern.PNNPattern
-
- getOutputNeurons() - Method in class org.encog.neural.pattern.SVMPattern
-
- getOutputNodes() - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- getOutputNormalizers() - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
- getOutputs() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
- getOutputs() - Method in interface org.encog.neural.freeform.FreeformNeuron
-
- getOutputSize() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getOutstarCount() - Method in class org.encog.neural.cpn.CPN
-
- getOwner() - Method in class org.encog.bot.browse.range.FormElement
-
- getOwner() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- getOwner() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- getOwner() - Method in class org.encog.ml.ea.opp.CompoundOperator
-
- getOwner() - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- getOwner() - Method in class org.encog.ml.prg.ProgramNode
-
- getOwner() - Method in class org.encog.ml.world.grid.GridState
-
- getOwner() - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
- getOwner() - Method in class org.encog.util.concurrency.job.JobUnitContext
-
- getPair() - Method in class org.encog.util.normalize.input.MLDataFieldHolder
-
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationBiPolar
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationClippedLinear
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationCompetitive
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationElliott
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationElliottSymmetric
- getParamNames() - Method in interface org.encog.engine.network.activation.ActivationFunction
-
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationGaussian
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationLinear
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationLOG
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationRamp
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationSigmoid
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationSIN
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationSoftMax
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationSteepenedSigmoid
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationStep
- getParamNames() - Method in class org.encog.engine.network.activation.ActivationTANH
- getParams() - Method in class org.encog.engine.network.activation.ActivationBiPolar
- getParams() - Method in class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
- getParams() - Method in class org.encog.engine.network.activation.ActivationClippedLinear
- getParams() - Method in class org.encog.engine.network.activation.ActivationCompetitive
- getParams() - Method in class org.encog.engine.network.activation.ActivationElliott
- getParams() - Method in class org.encog.engine.network.activation.ActivationElliottSymmetric
- getParams() - Method in interface org.encog.engine.network.activation.ActivationFunction
-
- getParams() - Method in class org.encog.engine.network.activation.ActivationGaussian
- getParams() - Method in class org.encog.engine.network.activation.ActivationLinear
- getParams() - Method in class org.encog.engine.network.activation.ActivationLOG
- getParams() - Method in class org.encog.engine.network.activation.ActivationRamp
- getParams() - Method in class org.encog.engine.network.activation.ActivationSigmoid
- getParams() - Method in class org.encog.engine.network.activation.ActivationSIN
- getParams() - Method in class org.encog.engine.network.activation.ActivationSoftMax
- getParams() - Method in class org.encog.engine.network.activation.ActivationSteepenedSigmoid
- getParams() - Method in class org.encog.engine.network.activation.ActivationStep
- getParams() - Method in class org.encog.engine.network.activation.ActivationTANH
- getParams() - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- getParams() - Method in class org.encog.ml.prg.extension.BasicTemplate
- getParams() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- getParams() - Method in class org.encog.ml.svm.SVM
-
- getParams() - Method in class org.encog.util.ParamsHolder
-
- getParent() - Method in class org.encog.app.generate.program.EncogTreeNode
-
- getParent() - Method in class org.encog.bot.browse.range.DocumentRange
-
- getParent() - Method in class org.encog.persist.EncogDirectoryPersistence
-
- getParents() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- getPattern() - Method in class org.encog.neural.prune.PruneIncremental
-
- getPeak() - Method in class org.encog.mathutil.rbf.BasicRBF
-
Get the center of this RBD.
- getPeak() - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
Get the center of this RBD.
- getPercent() - Method in class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
-
- getPercent() - Method in class org.encog.app.analyst.script.segregate.AnalystSegregateTarget
-
- getPercent() - Method in class org.encog.ml.data.versatile.division.DataDivision
-
- getPeriods() - Method in class org.encog.app.quant.indicators.Indicator
-
- getPeriods() - Method in class org.encog.app.quant.indicators.MovingAverage
-
- getPeriods() - Method in class org.encog.app.quant.indicators.predictive.BestClose
-
- getPeriods() - Method in class org.encog.app.quant.indicators.predictive.BestReturn
-
- getPersistClassString() - Method in class org.encog.ca.universe.basic.PersistBasicUniverse
-
- getPersistClassString() - Method in class org.encog.ml.bayesian.PersistBayes
- getPersistClassString() - Method in class org.encog.ml.hmm.PersistHMM
- getPersistClassString() - Method in class org.encog.ml.prg.PersistPrgPopulation
- getPersistClassString() - Method in class org.encog.ml.svm.PersistSVM
- getPersistClassString() - Method in class org.encog.neural.art.PersistART1
- getPersistClassString() - Method in class org.encog.neural.bam.PersistBAM
- getPersistClassString() - Method in class org.encog.neural.cpn.PersistCPN
- getPersistClassString() - Method in class org.encog.neural.neat.PersistNEATPopulation
-
- getPersistClassString() - Method in class org.encog.neural.networks.PersistBasicNetwork
- getPersistClassString() - Method in class org.encog.neural.networks.training.propagation.PersistTrainingContinuation
- getPersistClassString() - Method in class org.encog.neural.pnn.PersistBasicPNN
- getPersistClassString() - Method in class org.encog.neural.rbf.PersistRBFNetwork
- getPersistClassString() - Method in class org.encog.neural.som.PersistSOM
- getPersistClassString() - Method in class org.encog.neural.thermal.PersistBoltzmann
- getPersistClassString() - Method in class org.encog.neural.thermal.PersistHopfield
- getPersistClassString() - Method in interface org.encog.persist.EncogPersistor
-
- getPersistor(Class<?>) - Method in class org.encog.persist.PersistorRegistry
-
Get a persistor.
- getPersistor(String) - Method in class org.encog.persist.PersistorRegistry
-
Get the persistor by name.
- getPhenotype() - Method in class org.encog.ml.genetic.MLMethodGenome
-
- getPhysics() - Method in class org.encog.ca.runner.BasicCARunner
-
- getPhysics() - Method in interface org.encog.ca.runner.CARunner
-
- getPi(int) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getPi() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getPivot() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Return pivot permutation vector
- getPixelMap() - Method in interface org.encog.util.downsample.Downsample
-
- getPixelMap() - Method in class org.encog.util.downsample.RGBDownsample
-
- getPluginDescription() - Method in interface org.encog.plugin.EncogPluginBase
-
- getPluginDescription() - Method in class org.encog.plugin.system.SystemActivationPlugin
- getPluginDescription() - Method in class org.encog.plugin.system.SystemLoggingPlugin
- getPluginDescription() - Method in class org.encog.plugin.system.SystemMethodsPlugin
- getPluginDescription() - Method in class org.encog.plugin.system.SystemTrainingPlugin
- getPluginName() - Method in interface org.encog.plugin.EncogPluginBase
-
- getPluginName() - Method in class org.encog.plugin.system.SystemActivationPlugin
- getPluginName() - Method in class org.encog.plugin.system.SystemLoggingPlugin
- getPluginName() - Method in class org.encog.plugin.system.SystemMethodsPlugin
- getPluginName() - Method in class org.encog.plugin.system.SystemTrainingPlugin
- getPlugins() - Method in class org.encog.Encog
-
Get a list of the registered plugins.
- getPluginServiceType() - Method in interface org.encog.plugin.EncogPluginBase
-
- getPluginServiceType() - Method in class org.encog.plugin.system.SystemActivationPlugin
- getPluginServiceType() - Method in class org.encog.plugin.system.SystemLoggingPlugin
-
- getPluginServiceType() - Method in class org.encog.plugin.system.SystemMethodsPlugin
- getPluginServiceType() - Method in class org.encog.plugin.system.SystemTrainingPlugin
- getPluginType() - Method in interface org.encog.plugin.EncogPluginBase
-
- getPluginType() - Method in class org.encog.plugin.system.SystemActivationPlugin
-
- getPluginType() - Method in class org.encog.plugin.system.SystemLoggingPlugin
-
- getPluginType() - Method in class org.encog.plugin.system.SystemMethodsPlugin
-
- getPluginType() - Method in class org.encog.plugin.system.SystemTrainingPlugin
-
- getPoints() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getPointsPerSide() - Method in class org.encog.mathutil.matrices.hessian.HessianFD
-
- getPolicy() - Method in class org.encog.ml.world.basic.BasicAgent
-
- getPolicy() - Method in interface org.encog.ml.world.WorldAgent
-
- getPolicyValue() - Method in class org.encog.ml.world.basic.BasicState
-
- getPolicyValue(State, Action) - Method in class org.encog.ml.world.basic.BasicWorld
-
- getPolicyValue() - Method in interface org.encog.ml.world.State
-
- getPolicyValue(State, Action) - Method in interface org.encog.ml.world.World
-
- getPopulation() - Method in class org.encog.ml.ea.genome.BasicGenome
-
- getPopulation() - Method in interface org.encog.ml.ea.genome.Genome
-
- getPopulation() - Method in class org.encog.ml.ea.score.parallel.ParallelScore
-
- getPopulation() - Method in class org.encog.ml.ea.species.BasicSpecies
- getPopulation() - Method in interface org.encog.ml.ea.species.Species
-
- getPopulation() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getPopulation() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getPopulationSize() - Method in class org.encog.ml.ea.population.BasicPopulation
- getPopulationSize() - Method in interface org.encog.ml.ea.population.Population
-
- getPopulationSize() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Returns the swarm size.
- getPossibleTypes() - Method in class org.encog.ml.prg.extension.ParamTemplate
-
- getPostActivation() - Method in class org.encog.neural.neat.NEATNetwork
-
- getPreActivation() - Method in class org.encog.neural.neat.NEATNetwork
-
- getPrecedence() - Method in class org.encog.ml.prg.extension.BasicTemplate
- getPrecedence() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- getPrecision() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getPrecision() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getPrecision() - Method in class org.encog.app.quant.loader.yahoo.YahooDownload
-
- getPrecision() - Method in class org.encog.app.quant.ninja.NinjaStreamWriter
-
- getPredict() - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- getPredictedFeatures() - Method in class org.encog.ml.model.EncogModel
-
- getPredictWindow() - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
- getPredictWindowSize() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getPriors() - Method in class org.encog.neural.pnn.BasicPNN
-
- getProbabilities() - Method in class org.encog.ml.hmm.distributions.DiscreteDistribution
-
- getProbability() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- getProbability() - Method in class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
- getProbability() - Method in class org.encog.ml.bayesian.query.sample.SamplingQuery
- getProbability() - Method in class org.encog.ml.bayesian.table.TableLine
-
- getProbability() - Method in class org.encog.ml.world.basic.BasicWorld
-
- getProbability() - Method in class org.encog.ml.world.SuccessorState
-
- getProbability() - Method in interface org.encog.ml.world.World
-
- getProbability() - Method in class org.encog.util.obj.ObjectHolder
-
- getProbabilityLeft() - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- getProbabilityReverse() - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- getProbabilityRight() - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- getProbabilitySame() - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- getProbabilitySuccess() - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- getProblem() - Method in class org.encog.ml.bayesian.query.BasicQuery
- getProblem() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
- getProblem() - Method in class org.encog.ml.svm.training.SVMTrain
-
- getProblemType() - Method in class org.encog.ensemble.adaboost.AdaBoost
-
- getProblemType() - Method in class org.encog.ensemble.bagging.Bagging
-
- getProblemType() - Method in class org.encog.ensemble.Ensemble
-
Return what type of problem this Ensemble is solving
- getProblemType() - Method in class org.encog.ensemble.stacking.Stacking
-
- getProcess() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getProgram() - Method in class org.encog.app.generate.program.EncogTreeNode
-
- getProp() - Method in class org.encog.app.analyst.commands.Cmd
-
- getProperties() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getProperties() - Method in class org.encog.Encog
-
- getProperties() - Method in class org.encog.ml.BasicML
-
- getProperties() - Method in interface org.encog.ml.MLProperties
-
- getProperty(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as an object.
- getProperty(String) - Method in class org.encog.ml.world.basic.BasicState
-
- getProperty(String) - Method in interface org.encog.ml.world.State
-
- getPropertyBoolean(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a boolean.
- getPropertyCSVFormat(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a format.
- getPropertyDouble(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a double.
- getPropertyDouble(String) - Method in class org.encog.ml.BasicML
-
Get the specified property as a double.
- getPropertyDouble(String) - Method in interface org.encog.ml.MLProperties
-
Get the specified property as a double.
- getPropertyFile(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a file.
- getPropertyFormat(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a format.
- getPropertyInt(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a int.
- getPropertyLong(String) - Method in class org.encog.ml.BasicML
-
Get the specified property as a long.
- getPropertyLong(String) - Method in interface org.encog.ml.MLProperties
-
Get the specified property as a long.
- getPropertyString(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a string.
- getPropertyString(String) - Method in class org.encog.ml.BasicML
-
Get the specified property as a string.
- getPropertyString(String) - Method in interface org.encog.ml.MLProperties
-
Get the specified property as a string.
- getPropertyTargetLanguage(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get the property as a target language.
- getPropertyURL(String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as a url.
- getQ() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition
-
Generate and return the (economy-sized) orthogonal factor
- getQuery() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- getR() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition
-
Return the upper triangular factor
- getRadius() - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodBubble
-
- getRadius() - Method in interface org.encog.neural.som.training.basic.neighborhood.NeighborhoodFunction
-
- getRadius() - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF
-
- getRadius() - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF1D
-
- getRadius() - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodSingle
-
The radius for this neighborhood function is always 1.
- getRaf() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getRandom() - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
- getRandom() - Method in interface org.encog.mathutil.randomize.Randomizer
-
- getRandom() - Method in class org.encog.ml.data.versatile.division.PerformDataDivision
-
- getRandomFactory() - Method in class org.encog.Encog
-
- getRandomFactory() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getRandomNumberFactory() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getRandomNumberFactory() - Method in class org.encog.neural.neat.NEATPopulation
-
- getRange() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getRange(int) - Method in class org.encog.mathutil.dimension.DimensionConstraint
-
Get the range (between upper and lower bound) for the specified
dimension.
- getRatioX() - Method in interface org.encog.util.downsample.Downsample
-
- getRatioX() - Method in class org.encog.util.downsample.RGBDownsample
-
- getRatioY() - Method in interface org.encog.util.downsample.Downsample
-
- getRatioY() - Method in class org.encog.util.downsample.RGBDownsample
-
- getRBF() - Method in class org.encog.neural.flat.FlatNetworkRBF
-
- getRBF() - Method in class org.encog.neural.rbf.RBFNetwork
-
Get the RBF's.
- getRBF() - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF
-
- getReal() - Method in class org.encog.mathutil.ComplexNumber
-
Real part of this Complex number
(the x-coordinate in rectangular coordinates).
- getRealEigenvalues() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition
-
Return the real parts of the eigenvalues.
- getRecord(long, MLDataPair) - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- getRecord(long, MLDataPair) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- getRecord(long, MLDataPair) - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
Read an individual record, specified by index, in random order.
- getRecord(long, MLDataPair) - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
Read an individual record, specified by index, in random order.
- getRecord(long, MLDataPair) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Read an individual record.
- getRecord(long, MLDataPair) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Read an individual record, specified by index, in random order.
- getRecord(long, MLDataPair) - Method in interface org.encog.ml.data.MLDataSet
-
Read an individual record, specified by index, in random order.
- getRecord(long, MLDataPair) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
Read an individual record, specified by index, in random order.
- getRecordBuffer() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getRecordCount() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getRecordCount() - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- getRecordCount() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- getRecordCount() - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
Determine the total number of records in the set.
- getRecordCount() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
Determine the total number of records in the set.
- getRecordCount() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- getRecordCount() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getRecordCount() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Determine the total number of records in the set.
- getRecordCount() - Method in interface org.encog.ml.data.MLDataSet
-
Determine the total number of records in the set.
- getRecordCount() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
Determine the total number of records in the set.
- getRecordCount() - Method in class org.encog.util.normalize.DataNormalization
-
- getRecordSize() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
- getRelaxationThreshold() - Method in class org.encog.neural.neat.NEATNetwork
-
- getReplaceThisNode() - Method in class org.encog.ml.tree.traverse.tasks.TaskReplaceNode
-
- getReplaceWith() - Method in class org.encog.ml.tree.traverse.tasks.TaskReplaceNode
-
- getReport() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getReport() - Method in class org.encog.ml.model.EncogModel
-
- getReport() - Method in class org.encog.util.normalize.DataNormalization
-
- getReportInterval() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getResourceName() - Method in class org.encog.util.normalize.input.InputFieldEncogCollection
-
- getResourceName() - Method in class org.encog.util.normalize.target.NormalizationStorageEncogCollection
-
- getResult() - Method in class org.encog.ml.bayesian.table.TableLine
-
- getResult() - Method in class org.encog.ml.data.buffer.MemoryDataLoader
-
- getResult() - Method in class org.encog.ml.prg.EncogProgramContext
-
- getResult() - Method in class org.encog.ml.tree.traverse.tasks.TaskGetNodeIndex
-
- getResults() - Method in class org.encog.neural.prune.PruneIncremental
-
- getReturnType() - Method in class org.encog.ml.prg.EncogProgram
-
- getReturnValue() - Method in class org.encog.ml.prg.extension.BasicTemplate
- getReturnValue() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- getRevertData() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getReward() - Method in class org.encog.ml.world.basic.BasicState
-
- getReward() - Method in interface org.encog.ml.world.State
-
- getRewriteRules() - Method in class org.encog.ml.ea.rules.BasicRuleHolder
- getRewriteRules() - Method in interface org.encog.ml.ea.rules.RuleHolder
-
- getRms() - Method in class org.encog.mathutil.NumericRange
-
- getRnd() - Method in class org.encog.ml.data.cross.KFoldCrossvalidation
-
- getRoot() - Method in class org.encog.ml.graph.BasicGraph
-
- getRootNode() - Method in class org.encog.ml.prg.EncogProgram
-
- getRounds() - Method in class org.encog.ml.ea.opp.selection.TournamentSelection
-
- getRow(int) - Method in class org.encog.mathutil.matrices.Matrix
-
Get the specified row as a sub-matrix.
- getRow() - Method in class org.encog.ml.world.grid.GridState
-
- getRowMovement() - Method in class org.encog.ca.program.basic.Movement
-
- getRows() - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- getRows() - Method in interface org.encog.ca.universe.Universe
-
- getRows() - Method in class org.encog.mathutil.matrices.Matrix
-
Get the number of rows in the matrix.
- getRows() - Method in class org.encog.ml.world.grid.GridWorld
-
- getRPROPType() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
- getRules() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- getRules() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getRunCycles() - Method in class org.encog.neural.pattern.BoltzmannPattern
-
- getRunCycles() - Method in class org.encog.neural.thermal.BoltzmannMachine
-
- getRunningCounts() - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
- getS() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Return the diagonal matrix of singular values
- getSamples() - Method in class org.encog.mathutil.NumericRange
-
- getSamples() - Method in class org.encog.neural.pnn.BasicPNN
-
- getSampleSize() - Method in class org.encog.ml.bayesian.query.sample.SamplingQuery
-
- getSampleSize() - Method in class org.encog.util.normalize.segregate.index.IndexSampleSegregator
-
- getScore() - Method in class org.encog.ca.runner.BasicCARunner
-
- getScore() - Method in interface org.encog.ca.runner.CARunner
-
- getScore() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- getScore() - Method in class org.encog.ml.data.cross.DataFold
-
- getScore() - Method in class org.encog.ml.ea.genome.BasicGenome
-
- getScore() - Method in interface org.encog.ml.ea.genome.Genome
-
- getScore() - Method in class org.encog.ml.fitness.FitnessObjective
-
- getScore() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getScoreAdjusters() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getScoreAdjusters() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getScoreFunction() - Method in class org.encog.ml.ea.score.parallel.ParallelScore
-
- getScoreFunction() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getScoreFunction() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getScript() - Method in class org.encog.app.analyst.commands.Cmd
-
- getScript() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- getScript() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getScript() - Method in class org.encog.app.analyst.script.preprocess.AnalystPreprocess
-
- getSd() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- getSearch() - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
- getSection() - Method in class org.encog.app.analyst.script.prop.PropertyEntry
-
- getSectionName() - Method in class org.encog.persist.EncogFileSection
-
- getSeed() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
- getSegregate() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getSegregateTargets() - Method in class org.encog.app.analyst.script.segregate.AnalystSegregate
-
- getSegregators() - Method in class org.encog.util.normalize.DataNormalization
-
- getSelection() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getSelection() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getSelectionComparator() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Get the comparator that is used to choose the "best" genome for
selection, as opposed to the "true best".
- getSelectionComparator() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Get the comparator that is used to choose the "best" genome for
selection, as opposed to the "true best".
- getSeparator() - Method in class org.encog.util.csv.CSVFormat
-
- getSequence(int) - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
- getSequence(int) - Method in interface org.encog.ml.data.MLSequenceSet
-
Get an individual sequence.
- getSequence() - Method in class org.encog.ml.data.temporal.TemporalPoint
-
- getSequenceCount() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
- getSequenceCount() - Method in interface org.encog.ml.data.MLSequenceSet
-
- getSequenceCount() - Method in class org.encog.ml.hmm.alog.KullbackLeiblerDistanceCalculator
-
- getSequenceFromDate(Date) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Create a sequence number from a time.
- getSequenceGrandularity() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getSequences() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
- getSequences() - Method in interface org.encog.ml.data.MLSequenceSet
-
- getShouldIgnoreExceptions() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getShouldIgnoreExceptions() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getShouldStop() - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
- getShrink() - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
- getSigma() - Method in class org.encog.ml.fitting.gaussian.GaussianFitting
-
- getSigma() - Method in class org.encog.neural.pnn.BasicPNN
-
- getSigmaHigh() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- getSigmaLow() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- getSignature() - Method in class org.encog.ml.prg.extension.BasicTemplate
-
- getSignificance() - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- getSignificance() - Method in class org.encog.ml.data.basic.BasicMLDataPair
-
Get the significance, 1.0 is neutral.
- getSignificance() - Method in interface org.encog.ml.data.MLDataPair
-
Get the significance, 1.0 is neutral.
- getSingularValues() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Return the one-dimensional array of singular values
- getSlice(int) - Method in class org.encog.app.analyst.util.CSVHeaders
-
Get the timeslice for the specified index.
- getSolution() - Method in class org.encog.ml.graph.search.AbstractGraphSearch
-
- getSolution() - Method in interface org.encog.ml.graph.search.GraphSearch
-
- getSortGenomes() - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- getSortOrder() - Method in class org.encog.app.analyst.csv.sort.SortCSV
-
- getSortType() - Method in class org.encog.app.analyst.csv.sort.SortedField
-
- getSource() - Method in class org.encog.app.analyst.script.DataField
-
- getSource() - Method in class org.encog.app.analyst.wizard.SourceElement
-
- getSource() - Method in class org.encog.bot.browse.range.DocumentRange
-
- getSource() - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
- getSource() - Method in interface org.encog.neural.freeform.FreeformConnection
-
- getSource() - Method in class org.encog.neural.hyperneat.substrate.SubstrateLink
-
- getSourceColumns() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- getSourceField() - Method in class org.encog.util.normalize.output.mapped.OutputFieldEncode
-
- getSourceField() - Method in class org.encog.util.normalize.output.OutputFieldGrouped
-
- getSourceField() - Method in class org.encog.util.normalize.segregate.RangeSegregator
-
- getSourceUniverse() - Method in interface org.encog.ca.program.CAProgram
-
- getSourceUniverse() - Method in class org.encog.ca.program.conway.ConwayProgram
-
- getSourceUniverse() - Method in class org.encog.ca.program.elementary.ElementaryCA
-
- getSourceUniverse() - Method in class org.encog.ca.program.generic.GenericCA
-
- getSpan(TimeUnit) - Method in class org.encog.util.time.TimeSpan
-
Get the time span specified by the unit.
- getSparseData() - Method in class org.encog.ml.data.sparse.SparseMLData
-
- getSparseIndex() - Method in class org.encog.ml.data.sparse.SparseMLData
-
- getSpeciation() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getSpeciation() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- getSpecies() - Method in class org.encog.ml.ea.genome.BasicGenome
-
- getSpecies() - Method in interface org.encog.ml.ea.genome.Genome
-
- getSpecies() - Method in class org.encog.ml.ea.population.BasicPopulation
- getSpecies() - Method in interface org.encog.ml.ea.population.Population
-
- getSSE() - Method in class org.encog.mathutil.matrices.hessian.BasicHessian
- getSSE() - Method in interface org.encog.mathutil.matrices.hessian.ComputeHessian
-
- getStackTrace(Throwable) - Static method in class org.encog.plugin.system.SystemLoggingPlugin
-
Create a stack trace.
- getStandardDeviation() - Method in class org.encog.app.analyst.script.DataField
-
- getStandardDeviation() - Method in class org.encog.mathutil.NumericRange
-
- getStartingIndex() - Method in class org.encog.util.normalize.segregate.index.IndexRangeSegregator
-
- getStartingIndex() - Method in class org.encog.util.normalize.segregate.index.IndexSampleSegregator
-
- getStartingPoint() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- getStartNode() - Method in class org.encog.ml.schedule.ScheduleGraph
-
- getStartTemperature() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- getState(int, int) - Method in class org.encog.ml.world.grid.GridWorld
-
- getState() - Method in class org.encog.ml.world.SuccessorState
-
- getStateCount() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getStateDistribution(int) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getStates() - Method in class org.encog.ml.world.basic.BasicWorld
-
- getStates() - Method in interface org.encog.ml.world.World
-
- getStatesForSequence(MLDataSet) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getStatesForSequence(MLDataSet) - Method in interface org.encog.ml.MLStateSequence
-
Get the sates for the given sequence.
- getStats() - Method in class org.encog.util.arrayutil.NormalizeArray
-
- getStatus() - Method in class org.encog.ml.data.buffer.BinaryDataLoader
-
- getStatus() - Method in class org.encog.ml.data.buffer.MemoryDataLoader
-
- getStopTemperature() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- getStorage() - Method in class org.encog.util.normalize.DataNormalization
-
- getStrategies() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
- getStrategies() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- getStrategies() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- getStrategies() - Method in class org.encog.ml.train.BasicTraining
-
- getStrategies() - Method in interface org.encog.ml.train.MLTrain
-
- getStrategies() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- getString(String, boolean, String) - Method in class org.encog.util.ParamsHolder
-
Get a param as a string.
- getStripEfficiency() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getStripLength() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getStripOpt() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getStructure() - Method in class org.encog.neural.networks.BasicNetwork
-
- getSubfieldCount() - Method in class org.encog.util.normalize.output.mapped.OutputFieldEncode
-
- getSubfieldCount() - Method in class org.encog.util.normalize.output.multiplicative.OutputFieldMultiplicative
-
- getSubfieldCount() - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
This is the total number of nominal items minus 1.
- getSubfieldCount() - Method in class org.encog.util.normalize.output.nominal.OutputOneOf
-
- getSubfieldCount() - Method in interface org.encog.util.normalize.output.OutputField
-
- getSubfieldCount() - Method in class org.encog.util.normalize.output.OutputFieldDirect
-
- getSubfieldCount() - Method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
- getSubfieldCount() - Method in class org.encog.util.normalize.output.zaxis.OutputFieldZAxis
-
- getSubfieldCount() - Method in class org.encog.util.normalize.output.zaxis.OutputFieldZAxisSynthetic
-
- getSubSectionName() - Method in class org.encog.persist.EncogFileSection
-
- getSubstrate() - Method in class org.encog.neural.neat.NEATPopulation
-
- getSum() - Method in class org.encog.neural.freeform.basic.BasicActivationSummation
- getSum() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
- getSum() - Method in interface org.encog.neural.freeform.FreeformNeuron
-
- getSum() - Method in interface org.encog.neural.freeform.InputSummation
-
- getSurvivalRate() - Method in class org.encog.neural.neat.NEATPopulation
-
- getSVMType() - Method in class org.encog.ml.svm.SVM
-
- getSymbol() - Method in class org.encog.ml.data.market.TickerSymbol
-
- getTable() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- getTable() - Method in class org.encog.ml.bayesian.bif.BIFDefinition
-
- getTag() - Method in class org.encog.bot.dataunit.TagDataUnit
-
- getTag() - Method in class org.encog.parse.tags.read.ReadTags
-
Return the last tag found, this is normally called just after the read
function returns a zero.
- getTarget() - Method in class org.encog.bot.browse.range.Link
-
- getTarget() - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
- getTarget() - Method in interface org.encog.neural.freeform.FreeformConnection
-
- getTarget() - Method in class org.encog.neural.hyperneat.substrate.SubstrateLink
-
- getTarget() - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
- getTargetField() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- getTargetLanguage() - Method in class org.encog.app.generate.EncogCodeGeneration
-
- getTargets() - Method in class org.encog.app.analyst.csv.segregate.SegregateCSV
-
- getTargetUniverse() - Method in interface org.encog.ca.program.CAProgram
-
- getTargetUniverse() - Method in class org.encog.ca.program.conway.ConwayProgram
-
- getTargetUniverse() - Method in class org.encog.ca.program.elementary.ElementaryCA
-
- getTargetUniverse() - Method in class org.encog.ca.program.generic.GenericCA
-
- getTask(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
Get the specified task.
- getTaskNumber() - Method in class org.encog.util.concurrency.job.JobUnitContext
-
- getTasks() - Method in class org.encog.app.analyst.script.AnalystScript
-
- getTemperature() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- getTemperature() - Method in class org.encog.neural.pattern.BoltzmannPattern
-
- getTemperature() - Method in class org.encog.neural.thermal.BoltzmannMachine
-
- getTemplate() - Method in class org.encog.ml.prg.ProgramNode
-
- getTemplateMap() - Method in class org.encog.ml.prg.extension.FunctionFactory
-
- getTemplatePath() - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
- getTemplatePath() - Method in class org.encog.app.generate.generators.mql4.GenerateMQL4
-
- getTemplatePath() - Method in class org.encog.app.generate.generators.ninja.GenerateNinjaScript
-
- getTempTraining(int) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Get the specified temp training.
- getTempTraining(int) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Get the specified temp training.
- getTempTraining(int) - Method in interface org.encog.neural.freeform.TempTrainingData
-
Get the specified temp training.
- getTestError() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getText() - Method in class org.encog.bot.dataunit.TextDataUnit
-
- getTextOnly() - Method in class org.encog.bot.browse.range.DocumentRange
-
Get the text from this range.
- getThreadCount() - Method in class org.encog.mathutil.matrices.hessian.HessianCR
-
- getThreadCount() - Method in class org.encog.ml.ea.score.parallel.ParallelScore
-
- getThreadCount() - Method in class org.encog.ml.ea.train.basic.BasicEA
- getThreadCount() - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
- getThreadCount() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- getThreadCount() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
- getThreadCount() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
- getThreadCount() - Method in class org.encog.util.concurrency.DetermineWorkload
-
- getThreadCount() - Method in class org.encog.util.concurrency.EngineConcurrency
- getThreadCount() - Method in class org.encog.util.concurrency.job.ConcurrentJob
- getThreadCount() - Method in interface org.encog.util.concurrency.MultiThreadable
-
- getThreshold() - Method in class org.encog.neural.thermal.BoltzmannMachine
-
- getThresholdHigh() - Method in class org.encog.engine.network.activation.ActivationRamp
-
- getThresholdLow() - Method in class org.encog.engine.network.activation.ActivationRamp
-
- getTicker() - Method in class org.encog.ml.data.market.loader.LoadedMarketData
-
- getTicker() - Method in class org.encog.ml.data.market.MarketDataDescription
-
- getTimeSlice() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- getTitle() - Method in class org.encog.bot.browse.WebPage
-
Get the title for this document.
- getTitle() - Method in class org.encog.bot.rss.RSSItem
-
Get the item title.
- getTo() - Method in class org.encog.ml.graph.BasicEdge
-
- getTo() - Method in class org.encog.neural.networks.NeuralDataMapping
-
- getTo() - Method in class org.encog.util.time.TimeSpan
-
- getToNeuron() - Method in class org.encog.neural.neat.NEATLink
-
- getToNeuronID() - Method in class org.encog.neural.neat.training.NEATLinkGene
-
- getTopErrors() - Method in class org.encog.neural.prune.PruneIncremental
-
- getTopNetworks() - Method in class org.encog.neural.prune.PruneIncremental
-
- getTotalConnections() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getTotalCount() - Method in class org.encog.neural.flat.FlatLayer
-
- getTotalDepth() - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
- getTotalWindowSize() - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- getTotalWords() - Method in class org.encog.util.text.BagOfWords
-
- getTrain() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- getTrainer() - Method in interface org.encog.ml.ea.opp.selection.SelectionOperator
-
- getTrainer() - Method in class org.encog.ml.ea.opp.selection.TournamentSelection
- getTrainer() - Method in class org.encog.ml.ea.opp.selection.TruncationSelection
- getTrainer() - Method in interface org.encog.neural.neat.training.opp.links.MutateLinkWeight
-
- getTrainer() - Method in class org.encog.neural.neat.training.opp.links.MutatePerturbLinkWeight
- getTrainer() - Method in class org.encog.neural.neat.training.opp.links.MutateResetLinkWeight
- getTrainer() - Method in class org.encog.neural.neat.training.opp.links.SelectFixed
-
- getTrainer() - Method in interface org.encog.neural.neat.training.opp.links.SelectLinks
-
- getTrainer() - Method in class org.encog.neural.neat.training.opp.links.SelectProportion
- getTraining() - Method in interface org.encog.ensemble.EnsembleML
-
- getTraining(MLMethod, MLDataSet) - Method in interface org.encog.ensemble.EnsembleTrainFactory
-
- getTraining() - Method in class org.encog.ensemble.GenericEnsembleML
-
- getTraining(MLMethod, MLDataSet) - Method in class org.encog.ensemble.training.BackpropagationFactory
-
- getTraining(MLMethod, MLDataSet) - Method in class org.encog.ensemble.training.LevenbergMarquardtFactory
-
- getTraining(MLMethod, MLDataSet) - Method in class org.encog.ensemble.training.ManhattanPropagationFactory
-
- getTraining(MLMethod, MLDataSet) - Method in class org.encog.ensemble.training.ResilientPropagationFactory
-
- getTraining(MLMethod, MLDataSet) - Method in class org.encog.ensemble.training.ScaledConjugateGradientFactory
-
- getTraining() - Method in class org.encog.ml.data.cross.DataFold
-
- getTraining() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Returns null, does not use a training set, rather uses a score function.
- getTraining() - Method in class org.encog.ml.fitting.gaussian.TrainGaussian
-
- getTraining() - Method in class org.encog.ml.fitting.linear.TrainLinearRegression
-
- getTraining() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- getTraining() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- getTraining() - Method in class org.encog.ml.train.BasicTraining
-
- getTraining() - Method in interface org.encog.ml.train.MLTrain
-
- getTraining() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
- getTraining() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- getTraining() - Method in class org.encog.neural.prune.PruneIncremental
-
- getTrainingDataset() - Method in class org.encog.ml.model.EncogModel
-
- getTrainingError() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getTrainingError() - Method in class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
- getTrainingSet(int) - Method in class org.encog.ensemble.Ensemble
-
Extract a specific training set from the Ensemble
- getTrainingSet() - Method in interface org.encog.ensemble.EnsembleML
-
- getTrainingSet() - Method in class org.encog.ensemble.GenericEnsembleML
-
- getTrainingType() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
-
- getTransitionProbability(int, int) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getTransitionProbability() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- getTrueValue() - Method in class org.encog.util.normalize.output.nominal.OutputOneOf
-
- getType() - Method in class org.encog.app.generate.program.EncogProgramArg
-
- getType() - Method in class org.encog.app.generate.program.EncogProgramNode
-
- getType() - Method in class org.encog.bot.browse.range.Input
-
- getType() - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- getType() - Method in class org.encog.parse.tags.Tag
-
- getTypes() - Method in class org.encog.ml.prg.opp.LevelHolder
-
- getU() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Return upper triangular factor
- getU() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Return the left singular vectors
- getUnderlying() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- getUniqueWords() - Method in class org.encog.util.text.BagOfWords
-
- getUniverse() - Method in class org.encog.ca.runner.BasicCARunner
-
- getUniverse() - Method in interface org.encog.ca.runner.CARunner
-
- getUnknownValues() - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- getUpdateValues() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
- getUpper() - Method in class org.encog.mathutil.dimension.DimensionConstraint
-
- getUpper(int) - Method in class org.encog.mathutil.dimension.DimensionConstraint
-
Get the upper bound for a specific dimension.
- getUrl() - Method in class org.encog.bot.browse.Address
-
- getUsedForNetworkInput() - Method in class org.encog.util.normalize.input.BasicInputField
-
- getUsedForNetworkInput() - Method in interface org.encog.util.normalize.input.InputField
-
- getUtility() - Method in class org.encog.app.analyst.EncogAnalyst
-
- getV() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition
-
Return the eigenvector matrix.
- getV() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Return the right singular vectors
- getValidation() - Method in class org.encog.ml.data.cross.DataFold
-
- getValidationDataset() - Method in class org.encog.ml.model.EncogModel
-
- getValidationError() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- getValidationError() - Method in class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
- getValue() - Method in class org.encog.app.generate.program.EncogProgramArg
-
- getValue() - Method in class org.encog.bot.browse.range.FormElement
-
- getValue() - Method in class org.encog.ml.bayesian.parse.ParsedEvent
-
- getValue() - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- getValue(int) - Method in class org.encog.util.normalize.input.BasicInputField
-
Not supported for this sort of class, may be implemented in subclasses.
- getValue(int) - Method in interface org.encog.util.normalize.input.InputField
-
Called for input field types that require an index to get the current
value.
- getValue(int) - Method in class org.encog.util.normalize.input.InputFieldArray1D
-
Get the value from the specified index.
- getValue(int) - Method in class org.encog.util.normalize.input.InputFieldArray2D
-
Read a value from the specified index.
- getValue() - Method in class org.encog.util.normalize.output.mapped.MappedRange
-
- getVariable(int) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Get a variable value by index.
- getVariable(String) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Get a variable value by name.
- getVariableIndex(String) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Get a variable index by name.
- getVariableName(int) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Get a variable name by index.
- getVariables() - Method in class org.encog.ml.prg.EncogProgram
-
- getVariableType() - Method in class org.encog.ml.prg.VariableMapping
-
- getVigilance() - Method in class org.encog.neural.art.ART1
-
- getVigilance() - Method in class org.encog.neural.pattern.ART1Pattern
-
- getVisited() - Method in class org.encog.ml.world.basic.BasicState
-
- getVisited() - Method in interface org.encog.ml.world.State
-
- getWeight() - Method in class org.encog.ml.fitness.FitnessObjective
-
- getWeight() - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
- getWeight() - Method in interface org.encog.neural.freeform.FreeformConnection
-
- getWeight() - Method in class org.encog.neural.neat.NEATLink
-
- getWeight() - Method in class org.encog.neural.neat.training.NEATLinkGene
-
- getWeight(int, int, int) - Method in class org.encog.neural.networks.BasicNetwork
-
Get the weight between the two layers.
- getWeight(int, int) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Get a weight.
- getWeightIndex() - Method in class org.encog.neural.flat.FlatNetwork
-
- getWeightMutation() - Method in class org.encog.neural.neat.training.opp.NEATMutateWeights
-
- getWeightRange() - Method in class org.encog.neural.neat.NEATPopulation
-
- getWeights() - Method in class org.encog.ml.fitting.gaussian.GaussianFitting
-
- getWeights() - Method in class org.encog.ml.fitting.linear.LinearRegression
-
- getWeights() - Method in class org.encog.neural.flat.FlatNetwork
-
- getWeights() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getWeights() - Method in class org.encog.neural.networks.training.cross.NetworkFold
-
- getWeights() - Method in class org.encog.neural.networks.training.propagation.GradientWorker
-
- getWeights() - Method in class org.encog.neural.som.SOM
-
- getWeights() - Method in class org.encog.neural.thermal.ThermalNetwork
-
- getWeightsAndBias() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getWeightsF1toF2() - Method in class org.encog.neural.art.ART1
-
- getWeightsF1toF2() - Method in class org.encog.neural.bam.BAM
-
- getWeightsF2toF1() - Method in class org.encog.neural.art.ART1
-
- getWeightsF2toF1() - Method in class org.encog.neural.bam.BAM
-
- getWeightsInputToInstar() - Method in class org.encog.neural.cpn.CPN
-
- getWeightsInstarToOutstar() - Method in class org.encog.neural.cpn.CPN
-
- getWeightValues() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
-
- getWhen() - Method in class org.encog.ml.data.market.loader.LoadedMarketData
-
- getWhen() - Method in class org.encog.ml.data.market.MarketPoint
-
- getWidth() - Method in class org.encog.mathutil.rbf.BasicRBF
- getWidth() - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
- getWidth() - Method in class org.encog.platformspecific.j2se.data.image.ImageMLDataSet
-
- getWidth() - Method in class org.encog.util.ImageSize
-
- getWinner() - Method in class org.encog.neural.art.ART1
-
- getWinnerCount() - Method in class org.encog.neural.cpn.CPN
-
- getWords() - Method in class org.encog.util.text.BagOfWords
-
- getWorld() - Method in interface org.encog.ml.world.AgentPolicy
-
- getWorld() - Method in class org.encog.ml.world.basic.BasicAgent
-
- getWorld() - Method in class org.encog.ml.world.grid.probability.GridAbstractProbability
-
- getWorld() - Method in class org.encog.ml.world.learning.mdp.MarkovDecisionProcess
-
- getWorld() - Method in interface org.encog.ml.world.WorldAgent
-
- getWorstDistance() - Method in class org.encog.neural.som.training.basic.BestMatchingUnit
-
- getX() - Method in class org.encog.mathutil.IntPair
-
- getX1() - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- getX2() - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- getX3() - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- getXMLText(Node) - Static method in class org.encog.bot.rss.RSS
-
Simple utility method that obtains the text of an XML node.
- getY() - Method in class org.encog.mathutil.IntPair
-
- getY1() - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- getY2() - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- getY3() - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- getYear(long) - Static method in class org.encog.util.time.NumericDateUtil
-
- getZoom() - Method in class org.encog.ca.visualize.basic.BasicCAVisualizer
-
- getZoom() - Method in interface org.encog.ca.visualize.CAVisualizer
-
- GlobalMinimumSearch - Class in org.encog.neural.networks.training.pnn
-
Search sigma's for a global minimum.
- GlobalMinimumSearch() - Constructor for class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- gradients - Variable in class org.encog.mathutil.matrices.hessian.BasicHessian
-
The gradients of the Hessian.
- gradients - Variable in class org.encog.neural.networks.training.propagation.Propagation
-
The gradients.
- GradientWorker - Class in org.encog.neural.networks.training.propagation
-
Worker class for the mulithreaded training of flat networks.
- GradientWorker(FlatNetwork, Propagation, MLDataSet, int, int, double[], ErrorFunction) - Constructor for class org.encog.neural.networks.training.propagation.GradientWorker
-
Construct a gradient worker.
- GraphSearch - Interface in org.encog.ml.graph.search
-
- Greedy - Class in org.encog.ml.train.strategy
-
A simple greedy strategy.
- Greedy() - Constructor for class org.encog.ml.train.strategy.Greedy
-
- GridAbstractProbability - Class in org.encog.ml.world.grid.probability
-
- GridAbstractProbability(GridWorld) - Constructor for class org.encog.ml.world.grid.probability.GridAbstractProbability
-
- GridDeterministicProbability - Class in org.encog.ml.world.grid.probability
-
- GridDeterministicProbability(GridWorld) - Constructor for class org.encog.ml.world.grid.probability.GridDeterministicProbability
-
- GridState - Class in org.encog.ml.world.grid
-
- GridState(GridWorld, int, int, boolean) - Constructor for class org.encog.ml.world.grid.GridState
-
- GridStochasticProbability - Class in org.encog.ml.world.grid.probability
-
- GridStochasticProbability(GridWorld, double, double, double, double, double) - Constructor for class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- GridStochasticProbability(GridWorld) - Constructor for class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- GridWorld - Class in org.encog.ml.world.grid
-
- GridWorld(int, int) - Constructor for class org.encog.ml.world.grid.GridWorld
-
- GZIP - Static variable in class org.encog.util.text.Base64
-
Specify that data should be gzip-compressed in second bit.
- IDATA - Static variable in class org.encog.persist.PersistConst
-
idata.
- identity(int) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Return an identity matrix of the specified size.
- ImageMLData - Class in org.encog.platformspecific.j2se.data.image
-
An extension of the BasicNeuralData class that is designed to hold images for
input into a neural network.
- ImageMLData(Image) - Constructor for class org.encog.platformspecific.j2se.data.image.ImageMLData
-
Construct an object based on an image.
- ImageMLDataSet - Class in org.encog.platformspecific.j2se.data.image
-
Store a collection of images for training with a neural network.
- ImageMLDataSet(Downsample, boolean, double, double) - Constructor for class org.encog.platformspecific.j2se.data.image.ImageMLDataSet
-
Construct this class with the specified downsampler.
- ImageSize - Class in org.encog.util
-
Simple class to determine the size of an image.
- ImageSize(Image) - Constructor for class org.encog.util.ImageSize
-
Determine the size of an image.
- imageUpdate(Image, int, int, int, int, int) - Method in class org.encog.util.ImageSize
-
The image has been updated.
- increase(String) - Method in class org.encog.util.text.BagOfWords
-
- increaseCount() - Method in class org.encog.app.analyst.script.AnalystClassItem
-
Increase the count.
- increaseVisited() - Method in class org.encog.ml.world.basic.BasicState
-
- increaseVisited() - Method in interface org.encog.ml.world.State
-
- INDENT_SPACES - Static variable in class org.encog.app.generate.generators.AbstractGenerator
-
Default number of indent spaces.
- indentIn() - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Indent to the right one.
- indentLine(String) - Method in class org.encog.app.generate.generators.AbstractGenerator
-
Indent a line.
- indentOut() - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Indent to the left one.
- index - Variable in class org.encog.mathutil.libsvm.svm_node
-
- INDEX_DJIA - Static variable in class org.encog.app.quant.loader.yahoo.YahooDownload
-
The Dow Jones Industrial Average.
- INDEX_DOUBLE_CLOSE - Variable in class org.encog.ml.data.market.loader.LoadedMarketData
-
- INDEX_DOUBLE_HIGH - Variable in class org.encog.ml.data.market.loader.LoadedMarketData
-
- INDEX_DOUBLE_LOW - Variable in class org.encog.ml.data.market.loader.LoadedMarketData
-
- INDEX_DOUBLE_OPEN - Variable in class org.encog.ml.data.market.loader.LoadedMarketData
-
- INDEX_FILE - Static variable in class org.encog.util.http.URLUtility
-
The name of the usual default document.
- INDEX_NASDAQ - Static variable in class org.encog.app.quant.loader.yahoo.YahooDownload
-
The NASDAQ.
- INDEX_SP500 - Static variable in class org.encog.app.quant.loader.yahoo.YahooDownload
-
The S&P 500.
- IndexedNormalizer - Class in org.encog.ml.data.versatile.normalizers
-
Normalize ordinal/nominal values to a single value that is simply the index
of the class in the list.
- IndexedNormalizer() - Constructor for class org.encog.ml.data.versatile.normalizers.IndexedNormalizer
-
- indexOf(RandomVariable) - Method in class org.encog.mathutil.probability.vars.VariableList
-
- indexOfLargest(double[]) - Static method in class org.encog.util.EngineArray
-
- IndexRangeSegregator - Class in org.encog.util.normalize.segregate.index
-
An index segregator is used to segregate the data according to its index.
- IndexRangeSegregator() - Constructor for class org.encog.util.normalize.segregate.index.IndexRangeSegregator
-
Default constructor for reflection.
- IndexRangeSegregator(int, int) - Constructor for class org.encog.util.normalize.segregate.index.IndexRangeSegregator
-
Construct an index range segregator.
- IndexSampleSegregator - Class in org.encog.util.normalize.segregate.index
-
An index segregator is used to segregate the data according to its index.
- IndexSampleSegregator() - Constructor for class org.encog.util.normalize.segregate.index.IndexSampleSegregator
-
The default constructor, for reflection.
- IndexSampleSegregator(int, int, int) - Constructor for class org.encog.util.normalize.segregate.index.IndexSampleSegregator
-
Construct an index sample segregator.
- IndexSegregator - Class in org.encog.util.normalize.segregate.index
-
The index segregator.
- IndexSegregator() - Constructor for class org.encog.util.normalize.segregate.index.IndexSegregator
-
- Indicator - Class in org.encog.app.quant.indicators
-
An indicator, used by Encog.
- Indicator(String, boolean, boolean) - Constructor for class org.encog.app.quant.indicators.Indicator
-
Construct the indicator.
- init(ReadCSV, int, int) - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- init() - Method in class org.encog.app.analyst.script.AnalystScript
-
Init this script.
- init() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Init any internal structures.
- init(AnalystScript) - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
-
Init the normalized fields.
- init(Universe, CAProgram) - Method in class org.encog.ca.runner.BasicCARunner
-
- init(Universe, CAProgram) - Method in interface org.encog.ca.runner.CARunner
-
- init(BasicNetwork, MLDataSet) - Method in class org.encog.mathutil.matrices.hessian.BasicHessian
-
Init the class.
- init(BasicNetwork, MLDataSet) - Method in interface org.encog.mathutil.matrices.hessian.ComputeHessian
-
Init the class.
- init(BasicNetwork, MLDataSet) - Method in class org.encog.mathutil.matrices.hessian.HessianCR
-
Init the class.
- init(BasicNetwork, MLDataSet) - Method in class org.encog.mathutil.matrices.hessian.HessianFD
-
Init the class.
- init(TrainBayesian, BayesianNetwork, MLDataSet) - Method in interface org.encog.ml.bayesian.training.estimator.BayesEstimator
-
Init the estimator.
- init(TrainBayesian, BayesianNetwork, MLDataSet) - Method in class org.encog.ml.bayesian.training.estimator.EstimatorNone
-
Init the estimator.
- init(TrainBayesian, BayesianNetwork, MLDataSet) - Method in class org.encog.ml.bayesian.training.estimator.SimpleEstimator
-
Init the estimator.
- init(TrainBayesian, BayesianNetwork, MLDataSet) - Method in interface org.encog.ml.bayesian.training.search.k2.BayesSearch
-
Init the search object.
- init(TrainBayesian, BayesianNetwork, MLDataSet) - Method in class org.encog.ml.bayesian.training.search.k2.SearchK2
-
Init the search object.
- init(TrainBayesian, BayesianNetwork, MLDataSet) - Method in class org.encog.ml.bayesian.training.search.SearchNone
-
Init the search object.
- init(NormalizationHelper) - Method in class org.encog.ml.data.versatile.missing.MeanMissingHandler
-
Called by the normalizer to setup this handler.
- init(NormalizationHelper) - Method in interface org.encog.ml.data.versatile.missing.MissingHandler
-
Called by the normalizer to setup this handler.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.ea.opp.CompoundOperator
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in interface org.encog.ml.ea.opp.EvolutionaryOperator
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.ea.species.SingleSpeciation
-
Setup the speciation strategy.
- init(EvolutionaryAlgorithm) - Method in interface org.encog.ml.ea.species.Speciation
-
Setup the speciation strategy.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
Setup the speciation strategy.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.genetic.crossover.Splice
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.genetic.crossover.SpliceNoRepeat
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.genetic.mutate.MutatePerturb
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.genetic.mutate.MutateShuffle
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.prg.opp.ConstMutation
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.prg.opp.SubtreeCrossover
-
Called to setup the evolutionary operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.ml.prg.opp.SubtreeMutation
-
Called to setup the evolutionary operator.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.end.EndIterationsStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.end.EndMaxErrorStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.end.EndMinutesStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.Greedy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.HybridStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.RequiredImprovementStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.ResetStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.ml.train.strategy.StopTrainingStrategy
-
Initialize this strategy.
- init(MLTrain) - Method in interface org.encog.ml.train.strategy.Strategy
-
Initialize this strategy.
- init(FlatLayer[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Construct a flat network.
- init(EvolutionaryAlgorithm) - Method in interface org.encog.neural.neat.training.opp.links.MutateLinkWeight
-
Setup the link mutator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.neural.neat.training.opp.links.MutatePerturbLinkWeight
-
Setup the link mutator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.neural.neat.training.opp.links.MutateResetLinkWeight
-
Setup the link mutator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.neural.neat.training.opp.links.SelectFixed
-
Setup the selector.
- init(EvolutionaryAlgorithm) - Method in interface org.encog.neural.neat.training.opp.links.SelectLinks
-
Setup the selector.
- init(EvolutionaryAlgorithm) - Method in class org.encog.neural.neat.training.opp.links.SelectProportion
-
Setup the selector.
- init(EvolutionaryAlgorithm) - Method in class org.encog.neural.neat.training.opp.NEATCrossover
-
Init this operator.
- init(EvolutionaryAlgorithm) - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
Called to setup the evolutionary operator.
- init(MLTrain) - Method in class org.encog.neural.networks.training.strategy.RegularizationStrategy
-
- init(MLTrain) - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate
-
Initialize this strategy.
- init(MLTrain) - Method in class org.encog.neural.networks.training.strategy.SmartMomentum
-
Initialize this strategy.
- init() - Method in class org.encog.neural.prune.PruneIncremental
-
Init for prune.
- init(int, double[], double[]) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Init the network.
- init() - Method in class org.encog.util.arrayutil.NormalizedField
-
Init any internal structures.
- init() - Method in class org.encog.util.normalize.DataNormalization
-
- init(DataNormalization) - Method in class org.encog.util.normalize.segregate.index.IndexSegregator
-
Setup this class with the specified normalization object.
- init(DataNormalization) - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
Init the segregator with the owning normalization object.
- init(DataNormalization) - Method in class org.encog.util.normalize.segregate.RangeSegregator
-
Init the object.
- init(DataNormalization) - Method in interface org.encog.util.normalize.segregate.Segregator
-
Setup this object to use the specified normalization object.
- initForOutput() - Method in class org.encog.util.normalize.DataNormalization
-
Setup the row for output.
- initForPass() - Method in class org.encog.util.normalize.DataNormalization
-
Setup the row for output.
- INITIAL_DEPTH - Static variable in class org.encog.parse.PeekableInputStream
-
The depth to peek.
- INITIAL_STEP - Variable in class org.encog.mathutil.matrices.hessian.HessianFD
-
The initial step size for dStep.
- initMembers() - Method in class org.encog.ensemble.adaboost.AdaBoost
-
- initMembers() - Method in class org.encog.ensemble.bagging.Bagging
-
- initMembers() - Method in class org.encog.ensemble.Ensemble
-
Initialise ensemble components
- initMembers() - Method in class org.encog.ensemble.stacking.Stacking
-
- initMembersBySplits(int) - Method in class org.encog.ensemble.Ensemble
-
- initOthers() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
Perform training method specific init.
- initOthers() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
Perform training method specific init.
- initOthers() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
- initOthers() - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
Perform training method specific init.
- initOthers() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Perform training method specific init.
- initOthers() - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
Unused.
- Input - Class in org.encog.bot.browse.range
-
A form element that represents for input for text.
- Input(WebPage) - Constructor for class org.encog.bot.browse.range.Input
-
Construct this Input element.
- INPUT_COUNT - Static variable in class org.encog.persist.PersistConst
-
The input count.
- InputField - Interface in org.encog.util.normalize.input
-
A Normalization input field.
- InputFieldArray1D - Class in org.encog.util.normalize.input
-
An input field that comes from a 1D array.
- InputFieldArray1D(boolean, double[]) - Constructor for class org.encog.util.normalize.input.InputFieldArray1D
-
Construct the 1D array field.
- InputFieldArray2D - Class in org.encog.util.normalize.input
-
An input field that comes from a 2D array.
- InputFieldArray2D(boolean, double[][], int) - Constructor for class org.encog.util.normalize.input.InputFieldArray2D
-
Construct a 2D array input field.
- InputFieldCSV - Class in org.encog.util.normalize.input
-
An input field based on a CSV file.
- InputFieldCSV() - Constructor for class org.encog.util.normalize.input.InputFieldCSV
-
Construct an InputFieldCSV with the default constructor.
- InputFieldCSV(boolean, File, int) - Constructor for class org.encog.util.normalize.input.InputFieldCSV
-
Construct a input field for a CSV file.
- InputFieldCSVText - Class in org.encog.util.normalize.input
-
An input field based on a CSV file.
- InputFieldCSVText() - Constructor for class org.encog.util.normalize.input.InputFieldCSVText
-
Construct an InputFieldCSVText with the default constructor.
- InputFieldCSVText(boolean, File, int) - Constructor for class org.encog.util.normalize.input.InputFieldCSVText
-
Construct a input field for a CSV file.
- InputFieldEncogCollection - Class in org.encog.util.normalize.input
-
- InputFieldEncogCollection() - Constructor for class org.encog.util.normalize.input.InputFieldEncogCollection
-
- InputFieldEncogCollection(String, int) - Constructor for class org.encog.util.normalize.input.InputFieldEncogCollection
-
- InputFieldMLDataSet - Class in org.encog.util.normalize.input
-
An input field based on an Encog NeuralDataSet.
- InputFieldMLDataSet(boolean, NeuralDataSet, int) - Constructor for class org.encog.util.normalize.input.InputFieldMLDataSet
-
Construct a input field based on a NeuralDataSet.
- InputSummation - Interface in org.encog.neural.freeform
-
Specifies how the inputs to a neuron are to be summed.
- InputSummationFactory - Interface in org.encog.neural.freeform.factory
-
Factory that creates input summations.
- inRange(double) - Method in class org.encog.util.normalize.output.mapped.MappedRange
-
Determine if the specified value is in the range.
- inRange(double) - Method in class org.encog.util.normalize.segregate.SegregationRange
-
Is this value within the range.
- INSTAR - Static variable in class org.encog.persist.PersistConst
-
Instar.
- int2Time(Date, int) - Static method in class org.encog.util.time.NumericDateUtil
-
- IntegerArrayGenome - Class in org.encog.ml.genetic.genome
-
A genome that is an array of discrete integer values.
- IntegerArrayGenome(int) - Constructor for class org.encog.ml.genetic.genome.IntegerArrayGenome
-
Construct the genome.
- IntegerArrayGenome(IntegerArrayGenome) - Constructor for class org.encog.ml.genetic.genome.IntegerArrayGenome
-
Construct the genome by copying another.
- IntegerArrayGenomeFactory - Class in org.encog.ml.genetic.genome
-
A factory to create integer genomes of a specific size.
- IntegerArrayGenomeFactory(int) - Constructor for class org.encog.ml.genetic.genome.IntegerArrayGenomeFactory
-
Create the integer genome of a fixed size.
- IntegerBalanceSegregator - Class in org.encog.util.normalize.segregate
-
Balance based on an input value.
- IntegerBalanceSegregator(InputField, int) - Constructor for class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
Construct an integer balance segregator.
- IntegerBalanceSegregator() - Constructor for class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
Default constructor.
- IntPair - Class in org.encog.mathutil
-
- IntPair(int, int) - Constructor for class org.encog.mathutil.IntPair
-
- IntRange - Class in org.encog.mathutil
-
A range of integers.
- IntRange(int, int) - Constructor for class org.encog.mathutil.IntRange
-
Construct an integer range.
- inverse() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Solves a set of equation systems of type A * X = B.
- inverse() - Method in class org.encog.mathutil.matrices.Matrix
-
- inverseCholesky() - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition
-
- InverseMultiquadricFunction - Class in org.encog.mathutil.rbf
-
Multi-dimensional Inverse Multiquadric function.
- InverseMultiquadricFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.InverseMultiquadricFunction
-
Construct a single-dimension Inverse-Multiquadric function with the
specified peak, centers and widths.
- InverseMultiquadricFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.InverseMultiquadricFunction
-
Construct a multi-dimension Inverse-Multiquadric function with the
specified peak, centers and widths.
- InverseMultiquadricFunction(int) - Constructor for class org.encog.mathutil.rbf.InverseMultiquadricFunction
-
Create centered at zero, width 0, and peak 0.
- is(String, boolean) - Method in class org.encog.parse.tags.read.ReadTags
-
Checks to see if the next tag is the tag specified.
- isAnalyzed() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- isAscending() - Method in class org.encog.app.analyst.csv.sort.SortedField
-
- isAutoSend() - Method in class org.encog.bot.browse.range.FormElement
-
- isAutoSend() - Method in class org.encog.bot.browse.range.Input
-
- isBetterThan(double, double) - Method in class org.encog.ml.ea.sort.AbstractGenomeComparator
-
Determine if one score is better than the other.
- isBetterThan(double, double) - Method in interface org.encog.ml.ea.sort.GenomeComparator
-
Determine if one score is better than the other.
- isBetterThan(Genome, Genome) - Method in interface org.encog.ml.ea.sort.GenomeComparator
-
Determine if one genome is better than the other genome.
- isBetterThan(Genome, Genome) - Method in class org.encog.ml.ea.sort.MaximizeAdjustedScoreComp
-
Determine if one genome is better than the other genome.
- isBetterThan(Genome, Genome) - Method in class org.encog.ml.ea.sort.MaximizeScoreComp
-
Determine if one genome is better than the other genome.
- isBetterThan(Genome, Genome) - Method in class org.encog.ml.ea.sort.MinimizeAdjustedScoreComp
-
Determine if one genome is better than the other genome.
- isBetterThan(Genome, Genome) - Method in class org.encog.ml.ea.sort.MinimizeScoreComp
-
Determine if one genome is better than the other genome.
- isBias() - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- isBias() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
- isBias() - Method in interface org.encog.neural.freeform.FreeformNeuron
-
- isBoolean() - Method in class org.encog.mathutil.probability.vars.RandomVariable
-
- isBoolean() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- isBoolean() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- isBreakSpaces() - Method in class org.encog.util.text.BagOfWords
-
- isCalculated() - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- isClass() - Method in class org.encog.app.analyst.script.DataField
-
- isClassify() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- isClassify() - Method in enum org.encog.util.arrayutil.NormalizationAction
-
- isClassify() - Method in class org.encog.util.arrayutil.NormalizedField
-
- isCodeEmbedData() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isComplete() - Method in class org.encog.app.analyst.script.DataField
-
- isCondIndependent(BayesianEvent, BayesianEvent, BayesianEvent...) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- isConnected(int, int, int) - Method in class org.encog.neural.networks.BasicNetwork
-
Determine if the specified connection is enabled.
- isConnectionLimited() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
- isContinuous() - Method in class org.encog.ca.universe.basic.BasicCellFactory
-
- isContinuous() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- isDataReady() - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- isDefined(String, int) - Method in class org.encog.ml.prg.extension.FunctionFactory
-
Determine if an opcode is in the function factory.
- isDescendant(BayesianEvent, BayesianEvent) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Determine if one event is a descendant of another.
- isDiscrete() - Method in class org.encog.ca.universe.basic.BasicCellFactory
-
- isDiscrete() - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- isDuplicateLink(NEATGenome, long, long) - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
Determine if this is a duplicate link.
- isEmbedData() - Method in class org.encog.app.generate.EncogCodeGeneration
-
- isEmpty() - Method in class org.encog.util.datastruct.StackInt
-
- isEmpty() - Method in class org.encog.util.datastruct.StackObject
-
- isEmpty() - Method in class org.encog.util.datastruct.StackString
-
- isEnabled() - Method in class org.encog.neural.neat.training.NEATLinkGene
-
- isEnum() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- isExpectInputHeaders() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- isFixFlatSopt() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
- isFloat() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- isForceWinner() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
- isFull() - Method in class org.encog.util.arrayutil.WindowDouble
-
- isFullRank() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition
-
Is the matrix full rank?
- isGenerated(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
Determine if the specified file was generated.
- isGoalMet(BasicPath) - Method in interface org.encog.ml.graph.search.SearchGoal
-
- isGoalMet(BasicPath) - Method in class org.encog.ml.graph.search.SimpleDestinationGoal
-
- isGoalState(State) - Method in class org.encog.ml.world.basic.BasicWorld
-
- isGoalState(State) - Method in interface org.encog.ml.world.World
-
- isHasEnum() - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- isHasRelaxed() - Method in class org.encog.neural.neat.NEATNetwork
-
- isHigherPriority(BasicPath, BasicPath) - Method in class org.encog.ml.graph.search.AStarSearch
-
- isHigherPriority(BasicPath, BasicPath) - Method in class org.encog.ml.graph.search.BreadthFirstSearch
-
- isHigherPriority(BasicPath, BasicPath) - Method in class org.encog.ml.graph.search.DepthFirstSearch
-
- isHigherPriority(BasicPath, BasicPath) - Method in interface org.encog.ml.graph.search.Prioritizer
-
- isHyperNEAT() - Method in class org.encog.neural.neat.NEATPopulation
-
- isIdeal() - Method in class org.encog.util.normalize.output.BasicOutputField
-
- isIdeal() - Method in interface org.encog.util.normalize.output.OutputField
-
- isIdentifier() - Method in class org.encog.util.SimpleParser
-
- isIgnore() - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
- isIgnoreCase() - Method in class org.encog.util.text.BagOfWords
-
- isIgnored() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- isIncluded() - Method in class org.encog.util.normalize.segregate.SegregationRange
-
- isIncludeTargetField() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isInCluster(MLDataPair, int) - Method in class org.encog.ml.hmm.train.kmeans.Clusters
-
- isIndex() - Method in class org.encog.ml.bayesian.BayesianChoice
-
- isIndex() - Method in class org.encog.ml.bayesian.parse.ParsedChoice
-
- isInput() - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
- isInput() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- isInput() - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- isInputPresent(int) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Determine if the specified input is present.
- isInRange() - Method in class org.encog.util.normalize.output.nominal.NominalItem
-
- isInstanceOf(Class<?>, Class<?>) - Static method in class org.encog.util.obj.ReflectionUtil
-
Determine if one class is an instance of the other class.
- isInt() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- isInteger() - Method in class org.encog.app.analyst.script.DataField
-
- isLayerBiased(int) - Method in class org.encog.neural.networks.BasicNetwork
-
Determine if the specified layer is biased.
- isLeaf() - Method in class org.encog.ml.tree.basic.BasicTreeNode
-
- isLeaf() - Method in interface org.encog.ml.tree.TreeNode
-
- isLimited() - Method in class org.encog.neural.flat.FlatNetwork
-
- isLoadToMemory() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- isMultiThreaded() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Get the multi-threaded mode.
- isNaiveBayes() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isNeededEvidence() - Method in class org.encog.ml.bayesian.query.BasicQuery
-
- isNeuronNeeded(NEATGenome, long) - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
Determines if a neuron is still needed.
- isNonsingular() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Is the matrix nonsingular?
- isNormalizationEnabled() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- isNumeric() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- isOperator() - Method in enum org.encog.ml.prg.extension.NodeType
-
- isOSX() - Static method in class org.encog.Encog
-
- isOutput() - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
- isOutput() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- isPassThrough() - Method in class org.encog.ml.prg.extension.ParamTemplate
-
- isPointInRange(TemporalPoint) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Is the specified point within the range.
- isPossible(World, State, Action) - Method in interface org.encog.ml.world.PerformAction
-
- isPossibleReturnType(EncogProgramContext, ValueType) - Method in class org.encog.ml.prg.extension.BasicTemplate
-
Determines if the specified return type is a possible return type.
- isPossibleReturnType(EncogProgramContext, ValueType) - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
Determines if the specified return type is a possible return type.
- isPredict() - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- isPreprocess() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isPrimitive(Object) - Static method in class org.encog.util.obj.ReflectionUtil
-
Determine if the specified object is a primitive.
- isProduceOutputHeaders() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- isReady() - Method in class org.encog.util.arrayutil.VectorWindow
-
- isReal() - Method in class org.encog.app.analyst.script.DataField
-
- isRecurrent() - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
- isRecurrent() - Method in interface org.encog.neural.freeform.FreeformConnection
-
- isRegression() - Method in class org.encog.neural.pattern.SVMPattern
-
- isRunning() - Method in class org.encog.ca.runner.BasicCARunner
-
- isRunning() - Method in interface org.encog.ca.runner.CARunner
-
- isRunning() - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
- isSatisfied() - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- isSeparateClass() - Method in class org.encog.neural.pnn.AbstractPNN
-
- isShouldMinimize() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- isShuffle() - Method in class org.encog.ml.data.versatile.division.PerformDataDivision
-
- isSimple(Object) - Static method in class org.encog.util.obj.ReflectionUtil
-
Determine if an object is "simple", that is it should be persisted just
with a .tostring.
- isSingleThreaded() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
- isSPD() - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition
-
Is the matrix symmetric and positive definite?
- isSquare() - Method in class org.encog.mathutil.matrices.Matrix
-
- isStateBlocked(GridState) - Static method in class org.encog.ml.world.grid.GridWorld
-
- isString() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- isSupervised() - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- isSupervised() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- isSupervised() - Method in class org.encog.ml.data.basic.BasicMLDataPair
- isSupervised() - Method in class org.encog.ml.data.basic.BasicMLDataSet
- isSupervised() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
- isSupervised() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- isSupervised() - Method in class org.encog.ml.data.folded.FoldedDataSet
- isSupervised() - Method in interface org.encog.ml.data.MLDataPair
-
- isSupervised() - Method in interface org.encog.ml.data.MLDataSet
-
- isSupervised() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
- isSupported(MLMethod) - Static method in class org.encog.app.generate.EncogCodeGeneration
-
Is the specified method supported for code generation?
- isTaskBalance() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isTaskCluster() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isTaskNormalize() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isTaskRandomize() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isTaskSegregate() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- isTimeSeries() - Method in class org.encog.app.analyst.EncogAnalyst
-
- isTrained() - Method in class org.encog.neural.pnn.AbstractPNN
-
- isTrainingDone() - Method in class org.encog.ml.bayesian.training.TrainBayesian
- isTrainingDone() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
- isTrainingDone() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- isTrainingDone() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- isTrainingDone() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- isTrainingDone() - Method in class org.encog.ml.svm.training.SVMTrain
-
- isTrainingDone() - Method in class org.encog.ml.train.BasicTraining
-
- isTrainingDone() - Method in interface org.encog.ml.train.MLTrain
-
- isTrainingDone() - Method in class org.encog.neural.networks.training.nm.NelderMeadTraining
- isTrainingDone() - Method in class org.encog.neural.som.training.clustercopy.SOMClusterCopyTraining
-
- isUsedDefault() - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- isValid(int, int) - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- isValid(int, int) - Method in interface org.encog.ca.universe.Universe
-
- isValid(Genome) - Method in class org.encog.ml.ea.rules.BasicRuleHolder
-
Determine if the specified genome is valid according to the constraint rules.
- isValid(Genome) - Method in interface org.encog.ml.ea.rules.ConstraintRule
-
Is this genome valid?
- isValid(Genome) - Method in interface org.encog.ml.ea.rules.RuleHolder
-
Determine if the specified genome is valid according to the constraint rules.
- isValid(String) - Method in class org.encog.util.csv.CSVFormat
-
Determine if the string can be parsed.
- isValidationMode() - Method in class org.encog.ml.ea.train.basic.BasicEA
- isValidationMode() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
- isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
Determine if the specified continuation object is valid to resume with.
- isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
Determine if the specified continuation object is valid to resume with.
- isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Determine if the specified continuation object is valid to resume with.
- isVariable() - Method in class org.encog.ml.prg.extension.BasicTemplate
- isVariable() - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
- isVariable() - Method in class org.encog.ml.prg.ProgramNode
-
- isVector() - Method in class org.encog.mathutil.matrices.Matrix
-
Determine if the matrix is a vector.
- isWhiteSpace() - Method in class org.encog.util.SimpleParser
-
- isZero() - Method in class org.encog.mathutil.matrices.Matrix
-
Return true if every value in the matrix is zero.
- iteration() - Method in interface org.encog.ca.program.CAProgram
-
- iteration() - Method in class org.encog.ca.program.conway.ConwayProgram
-
- iteration() - Method in class org.encog.ca.program.elementary.ElementaryCA
-
- iteration() - Method in class org.encog.ca.program.generic.GenericCA
-
- iteration() - Method in class org.encog.ca.runner.BasicCARunner
-
- iteration() - Method in interface org.encog.ca.runner.CARunner
-
- iteration() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Called to perform one cycle of the annealing process.
- iteration() - Method in interface org.encog.ml.bayesian.training.estimator.BayesEstimator
-
Perform an iteration.
- iteration() - Method in class org.encog.ml.bayesian.training.estimator.EstimatorNone
-
Perform an iteration.
- iteration() - Method in class org.encog.ml.bayesian.training.estimator.SimpleEstimator
-
Perform an iteration.
- iteration() - Method in interface org.encog.ml.bayesian.training.search.k2.BayesSearch
-
Perform an iteration.
- iteration() - Method in class org.encog.ml.bayesian.training.search.k2.SearchK2
-
Perform an iteration.
- iteration() - Method in class org.encog.ml.bayesian.training.search.SearchNone
-
Perform an iteration.
- iteration() - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
Perform one iteration of training.
- iteration() - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Perform a training iteration.
- iteration(int) - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Perform the specified number of training iterations.
- iteration() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
- iteration() - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Perform a training iteration.
- iteration() - Method in class org.encog.ml.fitting.gaussian.TrainGaussian
-
- iteration() - Method in class org.encog.ml.fitting.linear.TrainLinearRegression
-
- iteration() - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
Perform one training iteration.
- iteration() - Method in class org.encog.ml.graph.search.AbstractGraphSearch
-
- iteration() - Method in interface org.encog.ml.graph.search.GraphSearch
-
- iteration() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- iteration(int) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- iteration() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- iteration(int) - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- iteration() - Method in class org.encog.ml.kmeans.KMeansClustering
-
Perform a single training iteration.
- iteration(int) - Method in class org.encog.ml.kmeans.KMeansClustering
-
The number of iterations to perform.
- iteration() - Method in interface org.encog.ml.MLClustering
-
Perform the training iteration.
- iteration(int) - Method in interface org.encog.ml.MLClustering
-
Perform the specified number of training iterations.
- iteration() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
Perform one training iteration.
- iteration() - Method in class org.encog.ml.svm.training.SVMTrain
-
Perform either a train or a cross validation.
- iteration(int) - Method in class org.encog.ml.train.BasicTraining
-
Perform the specified number of training iterations.
- iteration() - Method in interface org.encog.ml.train.MLTrain
-
Perform one iteration of training.
- iteration(int) - Method in interface org.encog.ml.train.MLTrain
-
Perform a number of training iterations.
- iteration() - Method in class org.encog.ml.world.learning.mdp.ValueIteration
-
- iteration() - Method in class org.encog.neural.cpn.training.TrainInstar
-
Perform one iteration of training.
- iteration() - Method in class org.encog.neural.cpn.training.TrainOutstar
-
Perform one iteration of training.
- iteration() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Perform one iteration of training.
- iteration(int) - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Perform the specified number of training iterations.
- iteration() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
Perform one iteration of simulated annealing.
- iteration() - Method in class org.encog.neural.networks.training.cross.CrossValidationKFold
-
Perform one iteration.
- iteration() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
Perform one iteration.
- iteration() - Method in class org.encog.neural.networks.training.nm.NelderMeadTraining
-
Perform one iteration of training.
- iteration() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Perform one iteration of training.
- iteration() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Perform one training iteration.
- iteration(int) - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Perform the specified number of training iterations.
- iteration() - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
Perform one iteration.
- iteration() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Runs one PSO iteration over the whole population of networks.
- iteration() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
-
Perform one iteration of training.
- iteration() - Method in class org.encog.neural.rbf.training.SVDTraining
-
Perform one iteration.
- iteration() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Perform one training iteration.
- iteration() - Method in class org.encog.neural.som.training.clustercopy.SOMClusterCopyTraining
-
Perform one iteration of training.
- iterationComplete() - Method in interface org.encog.ca.universe.UniverseListener
-
- iterationPSO(boolean) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Internal method for the iteration of the swarm.
- iterator() - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- iterator() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- iterator() - Method in class org.encog.ml.data.basic.BasicMLDataSet
- iterator() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
- iterator() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- iterator() - Method in class org.encog.ml.data.folded.FoldedDataSet
- iterator() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
- m_bestErrors - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_bestVectorIndex - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_bestVectors - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_c1 - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_c2 - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_calculateScore - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_inertiaWeight - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_maxPosition - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_maxVelocity - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_multiThreaded - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_networks - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_populationSize - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_randomizer - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_va - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- m_velocities - Variable in class org.encog.neural.networks.training.pso.NeuralPSO
-
- magnitude(BiPolarNeuralData) - Method in class org.encog.neural.art.ART1
-
Get the magnitude of the specified input.
- main(String[]) - Static method in class org.encog.Test
-
- main(String[]) - Static method in class org.encog.util.text.DoubleString
-
- MajorityVoting - Class in org.encog.ensemble.aggregator
-
- MajorityVoting() - Constructor for class org.encog.ensemble.aggregator.MajorityVoting
-
- makeClass(NormalizationAction, int, int, int, int) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Make the classes based on numbers.
- makeClass(NormalizationAction, String[], double, double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Make the classes using names.
- makeClass(NormalizationAction, int, int, int, int) - Method in class org.encog.util.arrayutil.NormalizedField
-
Make a field to hold a class.
- makeClass(NormalizationAction, String[], double, double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Create a field that will be used to hold a class.
- makePassThrough() - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Make this a pass-through field.
- makePassThrough() - Method in class org.encog.util.arrayutil.NormalizedField
-
Make this a pass-through field.
- makeSparse(MLData) - Method in class org.encog.ml.svm.SVM
-
Convert regular Encog MLData into the "sparse" data needed by an SVM.
- ManhattanFactory - Class in org.encog.ml.factory.train
-
A factory for Manhattan training.
- ManhattanFactory() - Constructor for class org.encog.ml.factory.train.ManhattanFactory
-
- ManhattanPropagation - Class in org.encog.neural.networks.training.propagation.manhattan
-
One problem that the backpropagation technique has is that the magnitude of
the partial derivative may be calculated too large or too small.
- ManhattanPropagation(ContainsFlat, MLDataSet, double) - Constructor for class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
Construct a Manhattan propagation training object.
- ManhattanPropagationFactory - Class in org.encog.ensemble.training
-
- ManhattanPropagationFactory() - Constructor for class org.encog.ensemble.training.ManhattanPropagationFactory
-
- MappedRange - Class in org.encog.util.normalize.output.mapped
-
Simple class that is used internally to hold a range mapping.
- MappedRange(double, double, double) - Constructor for class org.encog.util.normalize.output.mapped.MappedRange
-
Construct the range mapping.
- mark() - Method in class org.encog.util.SimpleParser
-
- MarketDataDescription - Class in org.encog.ml.data.market
-
This class is used to describe the type of financial data that is needed.
- MarketDataDescription(TickerSymbol, MarketDataType, TemporalDataDescription.Type, ActivationFunction, boolean, boolean) - Constructor for class org.encog.ml.data.market.MarketDataDescription
-
Construct a MarketDataDescription item.
- MarketDataDescription(TickerSymbol, MarketDataType, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.ml.data.market.MarketDataDescription
-
Construct a MarketDataDescription item.
- MarketDataDescription(TickerSymbol, MarketDataType, boolean, boolean) - Constructor for class org.encog.ml.data.market.MarketDataDescription
-
Construct a MarketDataDescription item.
- MarketDataType - Enum in org.encog.ml.data.market
-
The types of market data that can be used.
- MarketError - Exception in org.encog.ml.data.market
-
Thrown when an error occurs processing market data.
- MarketError(String) - Constructor for exception org.encog.ml.data.market.MarketError
-
Construct a message exception.
- MarketError(Throwable) - Constructor for exception org.encog.ml.data.market.MarketError
-
Construct an exception that holds another exception.
- MarketLoader - Interface in org.encog.app.quant.loader
-
Common interface for market loaders.
- MarketLoader - Interface in org.encog.ml.data.market.loader
-
This interface defines a class that can be used to load external financial
data.
- MarketMLDataSet - Class in org.encog.ml.data.market
-
A data set that is designed to hold market data.
- MarketMLDataSet(MarketLoader, int, int) - Constructor for class org.encog.ml.data.market.MarketMLDataSet
-
Construct a market data set object.
- MarketPoint - Class in org.encog.ml.data.market
-
Hold one market datapoint.
- MarketPoint(Date, int) - Constructor for class org.encog.ml.data.market.MarketPoint
-
Construct a MarketPoint with the specified date and size.
- markGenerated(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
Mark the sepcified filename as generated.
- MarkovDecisionProcess - Class in org.encog.ml.world.learning.mdp
-
- MarkovDecisionProcess(World) - Constructor for class org.encog.ml.world.learning.mdp.MarkovDecisionProcess
-
- MarkovGenerator - Class in org.encog.ml.hmm.alog
-
This class is used to generate random sequences based on a Hidden Markov
Model.
- MarkovGenerator(HiddenMarkovModel) - Constructor for class org.encog.ml.hmm.alog.MarkovGenerator
-
- matchChoiceToRange(double) - Method in class org.encog.ml.bayesian.BayesianEvent
-
Match a continuous value to a discrete range.
- MathConst - Class in org.encog.mathutil
-
Math constants needed by Encog.
- Matrix - Class in org.encog.mathutil.matrices
-
This class implements a mathematical matrix.
- Matrix(boolean[][]) - Constructor for class org.encog.mathutil.matrices.Matrix
-
Construct a bipolar matrix from an array of booleans.
- Matrix(double[][]) - Constructor for class org.encog.mathutil.matrices.Matrix
-
Create a matrix from an array of doubles.
- Matrix(int, int) - Constructor for class org.encog.mathutil.matrices.Matrix
-
Create a blank array with the specified number of rows and columns.
- MATRIX - Static variable in class org.encog.persist.PersistConst
-
matrix.
- MatrixError - Exception in org.encog.mathutil.matrices
-
Used by the matrix classes to indicate an error.
- MatrixError(String) - Constructor for exception org.encog.mathutil.matrices.MatrixError
-
Construct this exception with a message.
- MatrixError(Throwable) - Constructor for exception org.encog.mathutil.matrices.MatrixError
-
Construct this exception with another exception.
- MatrixMath - Class in org.encog.mathutil.matrices
-
This class can perform many different mathematical operations on matrixes.
- MatrixMLDataSet - Class in org.encog.ml.data.versatile
-
The MatrixMLDataSet can use a large 2D matrix of doubles to internally hold
data.
- MatrixMLDataSet() - Constructor for class org.encog.ml.data.versatile.MatrixMLDataSet
-
The default constructor.
- MatrixMLDataSet(double[][], int, int) - Constructor for class org.encog.ml.data.versatile.MatrixMLDataSet
-
Construct the dataset with no mask.
- MatrixMLDataSet(double[][], int, int, int[]) - Constructor for class org.encog.ml.data.versatile.MatrixMLDataSet
-
Construct the dataset from a 2D double array..
- MatrixMLDataSet(MatrixMLDataSet, int[]) - Constructor for class org.encog.ml.data.versatile.MatrixMLDataSet
-
Construct the dataset from another matrix dataset.
- MatrixMLDataSet.MatrixMLDataSetIterator - Class in org.encog.ml.data.versatile
-
An iterator to be used with the MatrixMLDataSet.
- MatrixMLDataSet.MatrixMLDataSetIterator() - Constructor for class org.encog.ml.data.versatile.MatrixMLDataSet.MatrixMLDataSetIterator
-
- matrixToFlat(double[][], double[], int) - Method in class org.encog.neural.rbf.training.SVDTraining
-
Convert the matrix to flat.
- max(int) - Method in class org.encog.app.quant.util.BarBuffer
-
Get the max for the specified index.
- MAX(double, double) - Static method in class org.encog.neural.rbf.training.SVD
-
- MAX - Static variable in class org.encog.persist.PersistConst
-
- max(int) - Method in class org.encog.util.datastruct.StackInt
-
- max(double[]) - Static method in class org.encog.util.EngineArray
-
- max(int[]) - Static method in class org.encog.util.EngineArray
-
- MAX_LAYERS - Static variable in class org.encog.ml.factory.method.PNNFactory
-
The max layer count.
- MAX_LAYERS - Static variable in class org.encog.ml.factory.method.RBFNetworkFactory
-
The max layer count.
- MAX_LAYERS - Static variable in class org.encog.ml.factory.method.SRNFactory
-
The max layer count.
- MAX_LAYERS - Static variable in class org.encog.ml.factory.method.SVMFactory
-
The max layer count.
- MAX_LENGTH - Static variable in class org.encog.parse.tags.read.ReadTags
-
Maximum length string to read.
- MAX_MOMENTUM - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum
-
The maximum value that momentum can go to.
- MAX_PRECIS - Static variable in class org.encog.util.logging.DumpMatrix
-
Maximum precision.
- MAX_RAND - Static variable in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
The maximum rand number that the standard GCC based LCG will generate.
- MaximizeAdjustedScoreComp - Class in org.encog.ml.ea.sort
-
Use this comparator to maximize the adjusted score.
- MaximizeAdjustedScoreComp() - Constructor for class org.encog.ml.ea.sort.MaximizeAdjustedScoreComp
-
- MaximizeScoreComp - Class in org.encog.ml.ea.sort
-
Use this comparator to maximize the score.
- MaximizeScoreComp() - Constructor for class org.encog.ml.ea.sort.MaximizeScoreComp
-
- maxIndex(double[]) - Static method in class org.encog.mathutil.EncogMath
-
Get the index to the greatest number in a double array.
- maxIndex(double[]) - Static method in class org.encog.util.EngineArray
-
- maxIndex(int[]) - Static method in class org.encog.util.EngineArray
-
- maxOffspring() - Method in class org.encog.ml.ea.opp.OperationList
-
Determine the maximum number of offspring that might be produced by any
of the operators in this list.
- maxParents() - Method in class org.encog.ml.ea.opp.OperationList
-
Determine the maximum number of parents required by any of the operators
in the list.
- mean(int[]) - Static method in class org.encog.util.EngineArray
-
- mean(double[]) - Static method in class org.encog.util.EngineArray
-
- MeanAndModeMissing - Class in org.encog.app.analyst.missing
-
- MeanAndModeMissing() - Constructor for class org.encog.app.analyst.missing.MeanAndModeMissing
-
- MeanMissingHandler - Class in org.encog.ml.data.versatile.missing
-
Handle missing data by using the mean value of that column.
- MeanMissingHandler() - Constructor for class org.encog.ml.data.versatile.missing.MeanMissingHandler
-
- members - Variable in class org.encog.ensemble.Ensemble
-
- MEMORY_GIG - Static variable in class org.encog.util.Format
-
Bytes in a GB.
- MEMORY_K - Static variable in class org.encog.util.Format
-
Bytes in a KB.
- MEMORY_MEG - Static variable in class org.encog.util.Format
-
Bytes in a MB.
- MEMORY_TERA - Static variable in class org.encog.util.Format
-
Bytes in a TB.
- MemoryDataLoader - Class in org.encog.ml.data.buffer
-
This class is used, together with a CODEC, load training data from some
external file into an Encog memory-based training set.
- MemoryDataLoader(DataSetCODEC) - Constructor for class org.encog.ml.data.buffer.MemoryDataLoader
-
Construct a loader with the specified CODEC.
- MersenneTwisterGenerateRandom - Class in org.encog.mathutil.randomize.generate
-
The Mersenne twister is a pseudo random number generator developed in 1997 by Makoto Matsumoto and
Takuji Nishimura that is based on a matrix linear recurrence over a finite binary field F2.
- MersenneTwisterGenerateRandom() - Constructor for class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- MersenneTwisterGenerateRandom(long) - Constructor for class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- MersenneTwisterGenerateRandom(int[]) - Constructor for class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- MetaClassifier - Class in org.encog.ensemble.aggregator
-
- MetaClassifier(double, EnsembleMLMethodFactory, EnsembleTrainFactory) - Constructor for class org.encog.ensemble.aggregator.MetaClassifier
-
- MethodConfig - Interface in org.encog.ml.model.config
-
Define normalization for a specific method.
- MethodFactory - Interface in org.encog.ml
-
Factor MLMethods.
- MexicanHatFunction - Class in org.encog.mathutil.rbf
-
Multi-dimensional Mexican Hat, or Ricker wavelet, function.
- MexicanHatFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.MexicanHatFunction
-
Construct a single-dimension Mexican hat function with the specified
peak, centers and widths.
- MexicanHatFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.MexicanHatFunction
-
Construct a multi-dimension Mexican hat function with the specified peak,
centers and widths.
- MexicanHatFunction(int) - Constructor for class org.encog.mathutil.rbf.MexicanHatFunction
-
Create centered at zero, width 0, and peak 0.
- MILI_IN_SEC - Static variable in class org.encog.util.Format
-
How many miliseconds in a second.
- MILIS - Static variable in class org.encog.util.benchmark.Evaluate
-
Mili-seconds in a second.
- min(int) - Method in class org.encog.app.quant.util.BarBuffer
-
Get the min for the specified index.
- MIN(int, int) - Static method in class org.encog.neural.rbf.training.SVD
-
- MIN - Static variable in class org.encog.persist.PersistConst
-
- min(int) - Method in class org.encog.util.datastruct.StackInt
-
- min(double[]) - Static method in class org.encog.util.EngineArray
-
- min(int[]) - Static method in class org.encog.util.EngineArray
-
- MIN_EQ - Static variable in class org.encog.mathutil.Equilateral
-
The minimum number of fields to use equilateral encoding.
- MIN_EQ_CLASSES - Static variable in class org.encog.app.analyst.script.normalize.AnalystField
-
Minimum classes for encode using equilateral.
- MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum
-
The minimum improvement to adjust momentum.
- MIN_LINK - Static variable in class org.encog.neural.neat.training.opp.NEATMutateRemoveLink
-
Do not remove from genomes that have fewer than this number of links.
- MIN_WORTHWHILE - Static variable in class org.encog.util.concurrency.DetermineWorkload
-
What is the minimum number of workload entries for a thread to be
worthwhile.
- MinimizeAdjustedScoreComp - Class in org.encog.ml.ea.sort
-
Use this comparator to minimize the adjusted score.
- MinimizeAdjustedScoreComp() - Constructor for class org.encog.ml.ea.sort.MinimizeAdjustedScoreComp
-
- MinimizeScoreComp - Class in org.encog.ml.ea.sort
-
Use this comparator to minimize the score.
- MinimizeScoreComp() - Constructor for class org.encog.ml.ea.sort.MinimizeScoreComp
-
- minIndex(double[]) - Static method in class org.encog.mathutil.EncogMath
-
Get the index to the smallest number in a double array.
- minus(ComplexNumber) - Method in class org.encog.mathutil.ComplexNumber
-
Subtraction of Complex numbers (doesn't change this Complex number).
- minus(MLData) - Method in class org.encog.ml.data.basic.BasicMLData
-
Subtract one data element from another.
- MINUTE_OFFSET - Static variable in class org.encog.util.time.NumericDateUtil
-
- MINUTES_HOUR - Static variable in class org.encog.util.time.TimeSpan
-
Minutes in an hour.
- MissingHandler - Interface in org.encog.ml.data.versatile.missing
-
Specifies how to handle missing data.
- ML_CONFIG_ARCHITECTURE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:CONFIG_architecture".
- ML_CONFIG_EVAL_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:CONFIG_evalFile".
- ML_CONFIG_MACHINE_LEARNING_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:CONFIG_machineLearningFile".
- ML_CONFIG_OUTPUT_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:CONFIG_outputFile".
- ML_CONFIG_QUERY - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for "ML:CONFIG_query"
- ML_CONFIG_TRAINING_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:CONFIG_trainingFile".
- ML_CONFIG_TYPE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: = ML:CONFIG_type".
- ML_TRAIN_ARGUMENTS - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:TRAIN_arguments".
- ML_TRAIN_CROSS - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:TRAIN_cross".
- ML_TRAIN_TARGET_ERROR - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:TRAIN_targetError".
- ML_TRAIN_TYPE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "ML:TRAIN_type".
- MLActivationFactory - Class in org.encog.ml.factory
-
- MLActivationFactory() - Constructor for class org.encog.ml.factory.MLActivationFactory
-
- MLAutoAssocation - Interface in org.encog.ml
-
Defines a MLMethod that can handle autoassocation.
- MLClassification - Interface in org.encog.ml
-
This interface defines a MLMethod that is used for classification.
- MLCluster - Interface in org.encog.ml
-
Defines a cluster.
- MLClustering - Interface in org.encog.ml
-
A machine learning method that is used to break data into clusters.
- MLComplexData - Interface in org.encog.ml.data
-
This class implements a data object that can hold complex numbers.
- MLContext - Interface in org.encog.ml
-
Defines a MLMethod that can hold context.
- MLData - Interface in org.encog.ml.data
-
Defines an array of data.
- MLDataError - Exception in org.encog.ml.data
-
Used by the machine learning methods classes to indicate a data error.
- MLDataError(String) - Constructor for exception org.encog.ml.data.MLDataError
-
Construct a message exception.
- MLDataError(Throwable) - Constructor for exception org.encog.ml.data.MLDataError
-
Construct an exception that holds another exception.
- MLDataFieldHolder - Class in org.encog.util.normalize.input
-
Simple holder class used internally for Encog.
- MLDataFieldHolder(Iterator<MLDataPair>, InputFieldMLDataSet) - Constructor for class org.encog.util.normalize.input.MLDataFieldHolder
-
Construct the class.
- MLDataPair - Interface in org.encog.ml.data
-
Training data is stored in two ways, depending on if the data is for
supervised, or unsupervised training.
- MLDataSet - Interface in org.encog.ml.data
-
An interface designed to abstract classes that store machine learning data.
- MLEncodable - Interface in org.encog.ml
-
Defines a Machine Learning Method that can be encoded to a double array.
- MLEncodableCODEC - Class in org.encog.ml.genetic
-
A CODEC for IMLEncodable classes.
- MLEncodableCODEC() - Constructor for class org.encog.ml.genetic.MLEncodableCODEC
-
- MLError - Interface in org.encog.ml
-
Defines Machine Learning Method that can calculate an error based on a
data set.
- mlFactory - Variable in class org.encog.ensemble.Ensemble
-
- MLFactory - Interface in org.encog.ml
-
This interface defines the fact that a class, or object, is having the
ability to generate an Encog factory code from the objects instanciated
state.
- MLInput - Interface in org.encog.ml
-
Defines a MLMethod that accepts input.
- MLInputOutput - Interface in org.encog.ml
-
This is a convenience interface that combines MLInput and MLOutput.
- MLMethod - Interface in org.encog.ml
-
This interface is the base for all Encog Machine Learning methods.
- MLMethodFactory - Class in org.encog.ml.factory
-
This factory is used to create machine learning methods.
- MLMethodFactory() - Constructor for class org.encog.ml.factory.MLMethodFactory
-
- MLMethodGeneticAlgorithm - Class in org.encog.ml.genetic
-
Implements a genetic algorithm that allows an MLMethod that is encodable
(MLEncodable) to be trained.
- MLMethodGeneticAlgorithm(MethodFactory, CalculateScore, int) - Constructor for class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
Construct a method genetic algorithm.
- MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper - Class in org.encog.ml.genetic
-
Very simple class that implements a genetic algorithm.
- MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper(Population, CalculateScore) - Constructor for class org.encog.ml.genetic.MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper
-
Construct the helper.
- MLMethodGenome - Class in org.encog.ml.genetic
-
Implements a genome that allows a feedforward neural network to be trained
using a genetic algorithm.
- MLMethodGenome(MLEncodable) - Constructor for class org.encog.ml.genetic.MLMethodGenome
-
Construct a neural genome.
- MLMethodGenomeFactory - Class in org.encog.ml.genetic
-
A factory to create MLMethod based genomes.
- MLMethodGenomeFactory(MethodFactory, Population) - Constructor for class org.encog.ml.genetic.MLMethodGenomeFactory
-
Construct the genome factory.
- MLOutput - Interface in org.encog.ml
-
Defines a MLMethod that produces output.
- MLProperties - Interface in org.encog.ml
-
Defines a Machine Learning Method that holds properties.
- MLRegression - Interface in org.encog.ml
-
Defines a Machine Learning Method that supports regression.
- MLResettable - Interface in org.encog.ml
-
Defines a Machine Learning Method that can be reset to an untrained
starting point.
- MLSequenceSet - Interface in org.encog.ml.data
-
A sequence set is a collection of data sets.
- MLStateSequence - Interface in org.encog.ml
-
A state sequence ML method, for example a Hidden Markov Model.
- MLTrain - Interface in org.encog.ml.train
-
Defines a training method for a machine learning method.
- MLTrainFactory - Class in org.encog.ml.factory
-
This factory is used to create trainers for machine learning methods.
- MLTrainFactory() - Constructor for class org.encog.ml.factory.MLTrainFactory
-
- mod() - Method in class org.encog.mathutil.ComplexNumber
-
Modulus of this Complex number
(the distance from the origin in polar coordinates).
- Momentum - Interface in org.encog.neural.networks.training
-
Specifies that a training algorithm has the concept of a momentum.
- MOMENTUM_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum
-
How many cycles to accept before adjusting momentum.
- MOMENTUM_INCREASE - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum
-
How much to increase momentum by.
- MONTH_OFFSET - Static variable in class org.encog.util.time.NumericDateUtil
-
- MONTHS_YEAR - Static variable in class org.encog.util.time.TimeSpan
-
Months in a year.
- MOVE_2WAY - Static variable in class org.encog.ca.program.basic.Movement
-
- MOVE_4WAY - Static variable in class org.encog.ca.program.basic.Movement
-
- MOVE_8WAY - Static variable in class org.encog.ca.program.basic.Movement
-
- Movement - Class in org.encog.ca.program.basic
-
- Movement(int, int) - Constructor for class org.encog.ca.program.basic.Movement
-
- MovingAverage - Class in org.encog.app.quant.indicators
-
A simple moving average.
- MovingAverage(int, boolean) - Constructor for class org.encog.app.quant.indicators.MovingAverage
-
Construct this object.
- MSG - Static variable in class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- MU - Static variable in class org.encog.mathutil.randomize.generate.AbstractBoxMuller
-
The mean.
- mul(double[], double) - Method in class org.encog.mathutil.VectorAlgebra
-
v = k * v
The components of the vector are multiplied
by k.
- mul(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform a multiply on two expression values.
- mul() - Method in class org.encog.util.datastruct.StackInt
-
- mulRand(double[], double) - Method in class org.encog.mathutil.VectorAlgebra
-
v = k * U(0,1) * v
The components of the vector are multiplied
by k and a random number.
- MULT - Static variable in class org.encog.util.text.DoubleString
-
- MultiDimension - Class in org.encog.mathutil.dimension
-
Handle multi-dimensional integer-based dimensions.
- MultiDimension(int) - Constructor for class org.encog.mathutil.dimension.MultiDimension
-
Allocate a MultiDimension.
- MultiDimension(MultiDimension) - Constructor for class org.encog.mathutil.dimension.MultiDimension
-
- MultiLayerPerceptronFactory - Class in org.encog.ensemble.ml.mlp.factory
-
- MultiLayerPerceptronFactory() - Constructor for class org.encog.ensemble.ml.mlp.factory.MultiLayerPerceptronFactory
-
- MultiObjectiveFitness - Class in org.encog.ml.fitness
-
A multi-objective fitness function.
- MultiObjectiveFitness() - Constructor for class org.encog.ml.fitness.MultiObjectiveFitness
-
- MultiplicativeGroup - Class in org.encog.util.normalize.output.multiplicative
-
Used to group multiplicative fields together.
- MultiplicativeGroup() - Constructor for class org.encog.util.normalize.output.multiplicative.MultiplicativeGroup
-
- multiply(UniverseCell) - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- multiply(UniverseCell) - Method in interface org.encog.ca.universe.ContinuousCell
-
- multiply(double) - Method in class org.encog.mathutil.matrices.Matrix
-
Multiply every value in the matrix by the specified value.
- multiply(double[], double[]) - Method in class org.encog.mathutil.matrices.Matrix
-
Multiply every row by the specified vector.
- multiply(Matrix, double) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Return the result of multiplying every cell in the matrix by the
specified value.
- multiply(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Return the product of the first and second matrix.
- multiply(Matrix, double[]) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
- MultiplyWithCarryGenerateRandom - Class in org.encog.mathutil.randomize.generate
-
In Multiply with Carry (MWC) is a pseudo random number generator computer science, multiply-with-carry (MWC)
is a method invented by George Marsaglia for generating sequences of random integers based on an initial set
from two to many thousands of randomly chosen seed values.
- MultiplyWithCarryGenerateRandom(long) - Constructor for class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
-
- MultiplyWithCarryGenerateRandom() - Constructor for class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
-
- MultiplyWithCarryGenerateRandom(long[], long, int, long) - Constructor for class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
-
- MultiquadricFunction - Class in org.encog.mathutil.rbf
-
Multi-dimensional Multiquadric function.
- MultiquadricFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.MultiquadricFunction
-
Construct a single-dimension Multiquadric function with the specified
peak, centers and widths.
- MultiquadricFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.MultiquadricFunction
-
Construct a multi-dimension Multiquadric function with the specified
peak, centers and widths.
- MultiquadricFunction(int) - Constructor for class org.encog.mathutil.rbf.MultiquadricFunction
-
Create centered at zero, width 0, and peak 0.
- MultiThreadable - Interface in org.encog.util.concurrency
-
Defines that a class is multi-threadable.
- MUST_USE_IMAGE - Static variable in class org.encog.platformspecific.j2se.data.image.ImageMLDataSet
-
Error message to inform the caller that only ImageNeuralData objects can
be used with this collection.
- MutateLinkWeight - Interface in org.encog.neural.neat.training.opp.links
-
This interface defines various ways that a NEAT network can have its link
weights mutated.
- MutatePerturb - Class in org.encog.ml.genetic.mutate
-
A simple mutation based on random numbers.
- MutatePerturb(double) - Constructor for class org.encog.ml.genetic.mutate.MutatePerturb
-
Construct a perturb mutation.
- MutatePerturbLinkWeight - Class in org.encog.neural.neat.training.opp.links
-
Mutate weight links by perturbing their weights.
- MutatePerturbLinkWeight(double) - Constructor for class org.encog.neural.neat.training.opp.links.MutatePerturbLinkWeight
-
Construct the perturbing mutator.
- MutateResetLinkWeight - Class in org.encog.neural.neat.training.opp.links
-
Mutate weight links by reseting the weight to an entirely new value.
- MutateResetLinkWeight() - Constructor for class org.encog.neural.neat.training.opp.links.MutateResetLinkWeight
-
- MutateShuffle - Class in org.encog.ml.genetic.mutate
-
A simple mutation where genes are shuffled.
- MutateShuffle() - Constructor for class org.encog.ml.genetic.mutate.MutateShuffle
-
- mutateWeight(Random, NEATLinkGene, double) - Method in interface org.encog.neural.neat.training.opp.links.MutateLinkWeight
-
Perform the weight mutation on the specified link.
- mutateWeight(Random, NEATLinkGene, double) - Method in class org.encog.neural.neat.training.opp.links.MutatePerturbLinkWeight
-
Perform the weight mutation on the specified link.
- mutateWeight(Random, NEATLinkGene, double) - Method in class org.encog.neural.neat.training.opp.links.MutateResetLinkWeight
-
Perform the weight mutation on the specified link.
- N - Static variable in class org.encog.engine.network.activation.ActivationLinear
-
Default empty parameters.
- NAME - Static variable in class org.encog.app.quant.indicators.MovingAverage
-
The name of this indicator.
- NAME - Static variable in class org.encog.app.quant.indicators.predictive.BestClose
-
The name of this indicator.
- NAME - Static variable in class org.encog.app.quant.indicators.predictive.BestReturn
-
The name of this indicator.
- NAME - Static variable in class org.encog.persist.PersistConst
-
A name.
- NATIVE - Static variable in class org.encog.persist.PersistConst
-
Native.
- navigate(Form) - Method in class org.encog.bot.browse.Browser
-
Navigate to the specified form by performing a submit of that form.
- navigate(Form, Input) - Method in class org.encog.bot.browse.Browser
-
Navigate based on a form.
- navigate(Link) - Method in class org.encog.bot.browse.Browser
-
Navigate to a new page based on a link.
- navigate(String) - Method in class org.encog.bot.browse.Browser
-
Navigate based on a string URL.
- navigate(URL) - Method in class org.encog.bot.browse.Browser
-
Navigate to a page based on a URL object.
- navigate(URL, InputStream) - Method in class org.encog.bot.browse.Browser
-
Navigate to a page and post the specified data.
- NEATBaseGene - Class in org.encog.neural.neat.training
-
Defines a base class for NEAT genes.
- NEATBaseGene() - Constructor for class org.encog.neural.neat.training.NEATBaseGene
-
- NEATCODEC - Class in org.encog.neural.neat
-
This CODEC is used to create phenomes (NEATNetwork) objects using a genome
(NEATGenome).
- NEATCODEC() - Constructor for class org.encog.neural.neat.NEATCODEC
-
- NEATConfig - Class in org.encog.ml.model.config
-
Config class for EncogModel to use a NEAT neural network.
- NEATConfig() - Constructor for class org.encog.ml.model.config.NEATConfig
-
- NEATCrossover - Class in org.encog.neural.neat.training.opp
-
Crossover is performed by mixing the link genes between the parents to
produce an offspring.
- NEATCrossover() - Constructor for class org.encog.neural.neat.training.opp.NEATCrossover
-
- NEATFactory - Class in org.encog.ml.factory.method
-
A factor to create feedforward networks.
- NEATFactory() - Constructor for class org.encog.ml.factory.method.NEATFactory
-
- NEATGAFactory - Class in org.encog.ml.factory.train
-
A factory to create genetic algorithm trainers.
- NEATGAFactory() - Constructor for class org.encog.ml.factory.train.NEATGAFactory
-
- NEATGenome - Class in org.encog.neural.neat.training
-
Implements a NEAT genome.
- NEATGenome(NEATGenome) - Constructor for class org.encog.neural.neat.training.NEATGenome
-
Construct a genome by copying another.
- NEATGenome(List<NEATNeuronGene>, List<NEATLinkGene>, int, int) - Constructor for class org.encog.neural.neat.training.NEATGenome
-
Create a NEAT gnome.
- NEATGenome(Random, NEATPopulation, int, int, double) - Constructor for class org.encog.neural.neat.training.NEATGenome
-
Create a new genome with the specified connection density.
- NEATGenome() - Constructor for class org.encog.neural.neat.training.NEATGenome
-
Empty constructor for persistence.
- NEATGenomeFactory - Interface in org.encog.neural.neat
-
This interface defines additional methods defined to create NEAT genomes.
- NEATInnovation - Class in org.encog.neural.neat.training
-
Implements a NEAT innovation.
- NEATInnovation() - Constructor for class org.encog.neural.neat.training.NEATInnovation
-
Default constructor, used mainly for persistence.
- NEATInnovationList - Class in org.encog.neural.neat.training
-
Implements a NEAT innovation list.
- NEATInnovationList() - Constructor for class org.encog.neural.neat.training.NEATInnovationList
-
The default constructor, used mainly for persistance.
- NEATInnovationList(NEATPopulation) - Constructor for class org.encog.neural.neat.training.NEATInnovationList
-
Construct an innovation list, that includes the initial innovations.
- NEATInnovationType - Enum in org.encog.neural.neat.training
-
The type of NEAT innovation.
- NEATLink - Class in org.encog.neural.neat
-
Implements a link between two NEAT neurons.
- NEATLink(int, int, double) - Constructor for class org.encog.neural.neat.NEATLink
-
Construct a NEAT link.
- NEATLinkGene - Class in org.encog.neural.neat.training
-
Implements a NEAT link gene.
- NEATLinkGene() - Constructor for class org.encog.neural.neat.training.NEATLinkGene
-
Default constructor, used mainly for persistence.
- NEATLinkGene(long, long, boolean, long, double) - Constructor for class org.encog.neural.neat.training.NEATLinkGene
-
Construct a NEAT link gene.
- NEATLinkGene(NEATLinkGene) - Constructor for class org.encog.neural.neat.training.NEATLinkGene
-
- NEATMutateAddLink - Class in org.encog.neural.neat.training.opp
-
Mutates a NEAT genome by adding a link.
- NEATMutateAddLink() - Constructor for class org.encog.neural.neat.training.opp.NEATMutateAddLink
-
- NEATMutateAddNode - Class in org.encog.neural.neat.training.opp
-
Mutate a genome by adding a new node.
- NEATMutateAddNode() - Constructor for class org.encog.neural.neat.training.opp.NEATMutateAddNode
-
- NEATMutateRemoveLink - Class in org.encog.neural.neat.training.opp
-
Mutate a genome by removing a random link.
- NEATMutateRemoveLink() - Constructor for class org.encog.neural.neat.training.opp.NEATMutateRemoveLink
-
- NEATMutateWeights - Class in org.encog.neural.neat.training.opp
-
Mutate the weights of a genome.
- NEATMutateWeights(SelectLinks, MutateLinkWeight) - Constructor for class org.encog.neural.neat.training.opp.NEATMutateWeights
-
Construct a weight mutation operator.
- NEATMutation - Class in org.encog.neural.neat.training.opp
-
This class represents a NEAT mutation.
- NEATMutation() - Constructor for class org.encog.neural.neat.training.opp.NEATMutation
-
- NEATNetwork - Class in org.encog.neural.neat
-
NEAT networks relieve the programmer of the need to define the hidden layer
structure of the neural network.
- NEATNetwork(int, int, List<NEATLink>, ActivationFunction[]) - Constructor for class org.encog.neural.neat.NEATNetwork
-
Construct a NEAT network.
- NEATNeuronGene - Class in org.encog.neural.neat.training
-
Implements a NEAT neuron gene.
- NEATNeuronGene() - Constructor for class org.encog.neural.neat.training.NEATNeuronGene
-
The default constructor.
- NEATNeuronGene(NEATNeuronType, ActivationFunction, long, long) - Constructor for class org.encog.neural.neat.training.NEATNeuronGene
-
Construct a neuron gene.
- NEATNeuronGene(NEATNeuronGene) - Constructor for class org.encog.neural.neat.training.NEATNeuronGene
-
Construct this gene by comping another.
- NEATNeuronType - Enum in org.encog.neural.neat
-
The types of neurons supported by NEAT.
- NEATPopulation - Class in org.encog.neural.neat
-
A population for a NEAT or HyperNEAT system.
- NEATPopulation() - Constructor for class org.encog.neural.neat.NEATPopulation
-
An empty constructor for serialization.
- NEATPopulation(int, int, int) - Constructor for class org.encog.neural.neat.NEATPopulation
-
Construct a starting NEAT population.
- NEATPopulation(Substrate, int) - Constructor for class org.encog.neural.neat.NEATPopulation
-
Construct a starting HyperNEAT population.
- NEATUtil - Class in org.encog.neural.neat
-
NEAT does not make use of a special trainer.
- NEATUtil() - Constructor for class org.encog.neural.neat.NEATUtil
-
- needsTraining() - Method in class org.encog.ensemble.aggregator.Averaging
-
- needsTraining() - Method in class org.encog.ensemble.aggregator.MajorityVoting
-
- needsTraining() - Method in class org.encog.ensemble.aggregator.MetaClassifier
-
- needsTraining() - Method in interface org.encog.ensemble.EnsembleAggregator
-
- neg(double[]) - Method in class org.encog.mathutil.VectorAlgebra
-
v = -v
- NegateMissing - Class in org.encog.app.analyst.missing
-
- NegateMissing() - Constructor for class org.encog.app.analyst.missing.NegateMissing
-
- NEGATIVE_ETA - Static variable in class org.encog.neural.networks.training.propagation.resilient.RPROPConst
-
The NEGATIVE ETA value.
- NeighborhoodBubble - Class in org.encog.neural.som.training.basic.neighborhood
-
A neighborhood function that uses a simple bubble.
- NeighborhoodBubble(int) - Constructor for class org.encog.neural.som.training.basic.neighborhood.NeighborhoodBubble
-
Create a bubble neighborhood function that will return 1.0 (full update)
for any neuron that is plus or minus the width distance from the winning
neuron.
- NeighborhoodFunction - Interface in org.encog.neural.som.training.basic.neighborhood
-
Defines how a neighborhood function should work in competitive training.
- NeighborhoodRBF - Class in org.encog.neural.som.training.basic.neighborhood
-
Implements a multi-dimensional RBF neighborhood function.
- NeighborhoodRBF(RBFEnum, int, int) - Constructor for class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF
-
Construct a 2d neighborhood function based on the sizes for the
x and y dimensions.
- NeighborhoodRBF(int[], RBFEnum) - Constructor for class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF
-
Construct a multi-dimensional neighborhood function.
- NeighborhoodRBF1D - Class in org.encog.neural.som.training.basic.neighborhood
-
A neighborhood function based on an RBF function.
- NeighborhoodRBF1D(RadialBasisFunction) - Constructor for class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF1D
-
Construct the neighborhood function with the specified radial function.
- NeighborhoodRBF1D(RBFEnum) - Constructor for class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF1D
-
Construct a 1d neighborhood function.
- NeighborhoodSingle - Class in org.encog.neural.som.training.basic.neighborhood
-
A very simple neighborhood function that will return 1.0 (full effect) for
the winning neuron, and 0.0 (no change) for everything else.
- NeighborhoodSingle() - Constructor for class org.encog.neural.som.training.basic.neighborhood.NeighborhoodSingle
-
- NeighborhoodSOMFactory - Class in org.encog.ml.factory.train
-
Train an SOM network with a neighborhood method.
- NeighborhoodSOMFactory() - Constructor for class org.encog.ml.factory.train.NeighborhoodSOMFactory
-
- NelderMeadFactory - Class in org.encog.ml.factory.train
-
- NelderMeadFactory() - Constructor for class org.encog.ml.factory.train.NelderMeadFactory
-
- NelderMeadTraining - Class in org.encog.neural.networks.training.nm
-
The Nelder-Mead method is a commonly used parameter optimization method that
can be used for neural network training.
- NelderMeadTraining(BasicNetwork, MLDataSet) - Constructor for class org.encog.neural.networks.training.nm.NelderMeadTraining
-
Construct a Nelder Mead trainer with a step size of 100.
- NelderMeadTraining(BasicNetwork, MLDataSet, double) - Constructor for class org.encog.neural.networks.training.nm.NelderMeadTraining
-
Construct a Nelder Mead trainer with a definable step.
- network - Variable in class org.encog.mathutil.matrices.hessian.BasicHessian
-
The neural network that we would like to train.
- network - Variable in class org.encog.neural.networks.training.propagation.Propagation
-
The network to train.
- NetworkCODEC - Class in org.encog.neural.networks.structure
-
This class will extract the "long term memory" of a neural network, that is
the weights and bias values into an array.
- NetworkFold - Class in org.encog.neural.networks.training.cross
-
The network for one fold of a cross validation.
- NetworkFold(FlatNetwork) - Constructor for class org.encog.neural.networks.training.cross.NetworkFold
-
Construct a fold from the specified flat network.
- NetworkPattern - Enum in org.encog.neural.prune
-
Specify which network pattern to use.
- networkSize(MLMethod) - Static method in class org.encog.neural.networks.structure.NetworkCODEC
-
Determine the network size.
- networkToArray(MLMethod) - Static method in class org.encog.neural.networks.structure.NetworkCODEC
-
Convert to an array.
- networkToString(BasicNetwork) - Static method in class org.encog.neural.prune.PruneIncremental
-
Format the network as a human readable string that lists the hidden
layers.
- NeuralData - Interface in org.encog.neural.data
-
This is an alias class for Encog 2.5 compatibility.
- NeuralDataMapping - Class in org.encog.neural.networks
-
Used to map one neural data object to another.
- NeuralDataMapping() - Constructor for class org.encog.neural.networks.NeuralDataMapping
-
Construct the neural data mapping class, with null values.
- NeuralDataMapping(MLData, MLData) - Constructor for class org.encog.neural.networks.NeuralDataMapping
-
Construct the neural data mapping class with the specified values.
- NeuralDataPair - Interface in org.encog.neural.data
-
This is an alias class for Encog 2.5 compatibility.
- NeuralDataSet - Interface in org.encog.neural.data
-
This is an alias class for Encog 2.5 compatibility.
- NeuralDataSetCODEC - Class in org.encog.ml.data.buffer.codec
-
A CODEC that works with the NeuralDataSet class.
- NeuralDataSetCODEC(MLDataSet) - Constructor for class org.encog.ml.data.buffer.codec.NeuralDataSetCODEC
-
Construct a CODEC.
- NeuralNetworkError - Exception in org.encog.neural
-
Used by the neural network classes to indicate an error.
- NeuralNetworkError(String) - Constructor for exception org.encog.neural.NeuralNetworkError
-
Construct a message exception.
- NeuralNetworkError(Throwable) - Constructor for exception org.encog.neural.NeuralNetworkError
-
Construct an exception that holds another exception.
- NeuralNetworkError(String, Throwable) - Constructor for exception org.encog.neural.NeuralNetworkError
-
Construct an exception that holds another exception.
- NeuralNetworkPattern - Interface in org.encog.neural.pattern
-
Patterns are used to create common sorts of neural networks.
- NeuralPSO - Class in org.encog.neural.networks.training.pso
-
Iteratively trains a population of neural networks by applying
particle swarm optimisation (PSO).
- NeuralPSO(BasicNetwork, Randomizer, CalculateScore, int) - Constructor for class org.encog.neural.networks.training.pso.NeuralPSO
-
Constructor.
- NeuralPSO(BasicNetwork, MLDataSet) - Constructor for class org.encog.neural.networks.training.pso.NeuralPSO
-
Construct a PSO using a training set score function, 20 particles and the
NguyenWidrowRandomizer randomizer.
- NeuralPSOWorker - Class in org.encog.neural.networks.training.pso
-
PSO multi-treaded worker.
- NeuralPSOWorker(NeuralPSO, int, boolean) - Constructor for class org.encog.neural.networks.training.pso.NeuralPSOWorker
-
Constructor.
- NeuralSimulatedAnnealing - Class in org.encog.neural.networks.training.anneal
-
This class implements a simulated annealing training algorithm for neural
networks.
- NeuralSimulatedAnnealing(MLEncodable, CalculateScore, double, double, int) - Constructor for class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
Construct a simulated annleaing trainer for a encodable MLMethod.
- NeuralSimulatedAnnealingHelper - Class in org.encog.neural.networks.training.anneal
-
Simple class used by the neural simulated annealing.
- NeuralSimulatedAnnealingHelper(NeuralSimulatedAnnealing) - Constructor for class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper
-
Constructs this object.
- NeuralStructure - Class in org.encog.neural.networks.structure
-
Holds "cached" information about the structure of the neural network.
- NeuralStructure(BasicNetwork) - Constructor for class org.encog.neural.networks.structure.NeuralStructure
-
Construct a structure object for the specified network.
- NEURON_COUNT - Static variable in class org.encog.persist.PersistConst
-
Neurons.
- NEURONS - Static variable in class org.encog.persist.PersistConst
-
Neuron count.
- NeuronTask - Interface in org.encog.neural.freeform.task
-
Defines a task that is carried out for every neuron.
- neuronTypeToString(NEATNeuronType) - Static method in class org.encog.neural.neat.PersistNEATPopulation
-
Convert a NEATNeuronType enum to a string.
- newSequence() - Method in class org.encog.ml.hmm.alog.MarkovGenerator
-
- next(int) - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- next() - Method in class org.encog.ml.data.auto.AutoFloatDataSet.AutoFloatIterator
- next() - Method in class org.encog.ml.data.basic.BasicMLDataSet.BasicMLIterator
- next() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet.BasicMLSeqIterator
- next() - Method in class org.encog.ml.data.buffer.BufferedDataSetIterator
- next() - Method in class org.encog.ml.data.folded.FoldedIterator
- next() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet.MatrixMLDataSetIterator
- next() - Method in class org.encog.util.csv.ReadCSV
-
Read the next line.
- nextBoolean() - Method in class org.encog.mathutil.randomize.generate.BasicGenerateRandom
- nextBoolean() - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
- nextBoolean() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
- nextBoolean() - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
- nextBoolean() - Method in class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
- nextBoolean() - Method in class org.encog.mathutil.randomize.generate.SecureGenerateRandom
- nextDouble() - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
- nextDouble(double, double) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
Generate a random number in the specified range.
- nextDouble(double) - Method in class org.encog.mathutil.randomize.generate.AbstractGenerateRandom
-
The next random double up to a non-inclusive range.
- nextDouble(double, double) - Method in class org.encog.mathutil.randomize.generate.AbstractGenerateRandom
-
The next double between low (inclusive) and high (exclusive).
- nextDouble() - Method in class org.encog.mathutil.randomize.generate.BasicGenerateRandom
- nextDouble() - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
- nextDouble(double) - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
The next random double up to a non-inclusive range.
- nextDouble(double, double) - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
The next double between low (inclusive) and high (exclusive).
- nextDouble() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
- nextDouble() - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- nextDouble() - Method in class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
- nextDouble() - Method in class org.encog.mathutil.randomize.generate.SecureGenerateRandom
- nextFloat() - Method in class org.encog.mathutil.randomize.generate.BasicGenerateRandom
- nextFloat() - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
- nextFloat() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
- nextFloat() - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
- nextFloat() - Method in class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
- nextFloat() - Method in class org.encog.mathutil.randomize.generate.SecureGenerateRandom
- nextGaussian() - Method in class org.encog.mathutil.randomize.generate.AbstractBoxMuller
- nextGaussian() - Method in class org.encog.mathutil.randomize.generate.BasicGenerateRandom
- nextGaussian() - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
- nextGaussian() - Method in class org.encog.mathutil.randomize.generate.SecureGenerateRandom
- nextInt(int, int) - Method in class org.encog.mathutil.randomize.generate.AbstractGenerateRandom
-
The next int between low (inclusive) and high (exclusive).
- nextInt(int) - Method in class org.encog.mathutil.randomize.generate.AbstractGenerateRandom
-
The next random int up to a non-inclusive range.
- nextInt() - Method in class org.encog.mathutil.randomize.generate.BasicGenerateRandom
- nextInt() - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
- nextInt(int) - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
The next random int up to a non-inclusive range.
- nextInt(int, int) - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
The next int between low (inclusive) and high (exclusive).
- nextInt() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
- nextInt() - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
- nextInt() - Method in class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
- nextInt() - Method in class org.encog.mathutil.randomize.generate.SecureGenerateRandom
- nextLong() - Method in class org.encog.mathutil.randomize.generate.BasicGenerateRandom
- nextLong() - Method in interface org.encog.mathutil.randomize.generate.GenerateRandom
-
- nextLong() - Method in class org.encog.mathutil.randomize.generate.LinearCongruentialRandom
-
- nextLong() - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- nextLong() - Method in class org.encog.mathutil.randomize.generate.MultiplyWithCarryGenerateRandom
- nextLong() - Method in class org.encog.mathutil.randomize.generate.SecureGenerateRandom
- NguyenWidrowRandomizer - Class in org.encog.mathutil.randomize
-
Implementation of Nguyen-Widrow weight initialization.
- NguyenWidrowRandomizer() - Constructor for class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- NinjaFileConvert - Class in org.encog.app.quant.ninja
-
A simple class that shows how to convert financial data into the
form that NinjaTrader can recognize.
- NinjaFileConvert() - Constructor for class org.encog.app.quant.ninja.NinjaFileConvert
-
- NinjaStreamWriter - Class in org.encog.app.quant.ninja
-
Can be used from within NinjaTrader to export data.
- NinjaStreamWriter() - Constructor for class org.encog.app.quant.ninja.NinjaStreamWriter
-
Construct the object, and set the defaults.
- NO_BIAS_ACTIVATION - Static variable in class org.encog.neural.flat.FlatNetwork
-
The value that indicates that there is no bias activation.
- NO_OPTIONS - Static variable in class org.encog.util.text.Base64
-
No options specified.
- NO_PREC - Static variable in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
Defines a very low precidence.
- NodeType - Enum in org.encog.app.generate.program
-
The type of node.
- NodeType - Enum in org.encog.ml.prg.extension
-
The node type.
- NominalItem - Class in org.encog.util.normalize.output.nominal
-
A nominal item.
- NominalItem() - Constructor for class org.encog.util.normalize.output.nominal.NominalItem
-
Construct a empty range item.
- NominalItem(InputField, double, double) - Constructor for class org.encog.util.normalize.output.nominal.NominalItem
-
Create a nominal item.
- norm2() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Two norm
- NormalizationAction - Enum in org.encog.util.arrayutil
-
Normalization actions desired.
- NormalizationError - Exception in org.encog.util.normalize
-
Used for normalization errors.
- NormalizationError(String) - Constructor for exception org.encog.util.normalize.NormalizationError
-
Construct a message exception.
- NormalizationError(Throwable) - Constructor for exception org.encog.util.normalize.NormalizationError
-
Construct an exception that holds another exception.
- NormalizationHelper - Class in org.encog.ml.data.versatile
-
This class is used to perform normalizations for methods trained with the
versatile dataset.
- NormalizationHelper() - Constructor for class org.encog.ml.data.versatile.NormalizationHelper
-
- NormalizationStorage - Interface in org.encog.util.normalize.target
-
Defines a means by which normalized data can be stored.
- NormalizationStorageArray1D - Class in org.encog.util.normalize.target
-
Output the normalized data to a 1D array.
- NormalizationStorageArray1D() - Constructor for class org.encog.util.normalize.target.NormalizationStorageArray1D
-
- NormalizationStorageArray1D(double[]) - Constructor for class org.encog.util.normalize.target.NormalizationStorageArray1D
-
Construct an object to store to a 2D array.
- NormalizationStorageArray2D - Class in org.encog.util.normalize.target
-
Output the normalized data to a 2D array.
- NormalizationStorageArray2D(double[][]) - Constructor for class org.encog.util.normalize.target.NormalizationStorageArray2D
-
Construct an object to store to a 2D array.
- NormalizationStorageArray2D() - Constructor for class org.encog.util.normalize.target.NormalizationStorageArray2D
-
- NormalizationStorageCSV - Class in org.encog.util.normalize.target
-
Store normalized data to a CSV file.
- NormalizationStorageCSV(CSVFormat, File) - Constructor for class org.encog.util.normalize.target.NormalizationStorageCSV
-
Construct a CSV storage object from the specified file.
- NormalizationStorageCSV() - Constructor for class org.encog.util.normalize.target.NormalizationStorageCSV
-
- NormalizationStorageCSV(File) - Constructor for class org.encog.util.normalize.target.NormalizationStorageCSV
-
Construct a CSV storage object from the specified file.
- NormalizationStorageEncogCollection - Class in org.encog.util.normalize.target
-
- NormalizationStorageEncogCollection() - Constructor for class org.encog.util.normalize.target.NormalizationStorageEncogCollection
-
- NormalizationStorageNeuralDataSet - Class in org.encog.util.normalize.target
-
Store the normalized data to a neural data set.
- NormalizationStorageNeuralDataSet() - Constructor for class org.encog.util.normalize.target.NormalizationStorageNeuralDataSet
-
- NormalizationStorageNeuralDataSet(int, int) - Constructor for class org.encog.util.normalize.target.NormalizationStorageNeuralDataSet
-
Construct a new NeuralDataSet based on the parameters specified.
- NormalizationStorageNeuralDataSet(MLDataSet) - Constructor for class org.encog.util.normalize.target.NormalizationStorageNeuralDataSet
-
Construct a normalized neural storage class to hold data.
- NormalizationStrategy - Interface in org.encog.ml.data.versatile.normalizers.strategies
-
Defines the interface to a normalization strategy.
- normalize(File) - Method in class org.encog.app.analyst.csv.normalize.AnalystNormalizeCSV
-
Normalize the input file.
- normalize(File) - Method in class org.encog.app.analyst.csv.normalize.AnalystNormalizeToEGB
-
Normalize the input file.
- normalize(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Normalize the specified value.
- normalize() - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
Normalize the data set, and allocate memory to hold it.
- normalize(double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Normalize the specified value.
- NORMALIZE_CONFIG_SOURCE_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "NORMALIZE:CONFIG_sourceFile".
- NORMALIZE_CONFIG_TARGET_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "NORMALIZE:CONFIG_targetFile".
- NORMALIZE_MISSING_VALUES - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "NORMALIZE:CONFIG_missingValues".
- NormalizeArray - Class in org.encog.util.arrayutil
-
Normalization is the process where data is adjusted to be inside a range.
- NormalizeArray() - Constructor for class org.encog.util.arrayutil.NormalizeArray
-
Construct the object, default NormalizedHigh and NormalizedLow to 1 and
-1.
- normalizeBinary(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Normalize a binary number.
- normalizeColumn(ColumnDefinition, String, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.IndexedNormalizer
-
Normalize a column from a string.
- normalizeColumn(ColumnDefinition, double, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.IndexedNormalizer
-
Normalize a column from a double.
- normalizeColumn(ColumnDefinition, String, double[], int) - Method in interface org.encog.ml.data.versatile.normalizers.Normalizer
-
Normalize a column from a string.
- normalizeColumn(ColumnDefinition, double, double[], int) - Method in interface org.encog.ml.data.versatile.normalizers.Normalizer
-
Normalize a column from a double.
- normalizeColumn(ColumnDefinition, String, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.OneOfNNormalizer
-
Normalize a column from a string.
- normalizeColumn(ColumnDefinition, double, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.OneOfNNormalizer
-
Normalize a column from a double.
- normalizeColumn(ColumnDefinition, String, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.PassThroughNormalizer
-
Normalize a column from a string.
- normalizeColumn(ColumnDefinition, double, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.PassThroughNormalizer
-
- normalizeColumn(ColumnDefinition, String, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.RangeNormalizer
-
Normalize a column from a string.
- normalizeColumn(ColumnDefinition, double, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.RangeNormalizer
-
Normalize a column from a double.
- normalizeColumn(ColumnDefinition, String, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.RangeOrdinal
-
Normalize a column from a string.
- normalizeColumn(ColumnDefinition, double, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.RangeOrdinal
-
Normalize a column from a double.
- normalizeColumn(ColumnDefinition, boolean, String, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Normalize a column, with a string input.
- normalizeColumn(ColumnDefinition, boolean, double, double[], int) - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Normalize a column, with a double value.
- normalizeColumn(ColumnDefinition, boolean, String, double[], int) - Method in interface org.encog.ml.data.versatile.normalizers.strategies.NormalizationStrategy
-
Normalize a column, with a string input.
- normalizeColumn(ColumnDefinition, boolean, double, double[], int) - Method in interface org.encog.ml.data.versatile.normalizers.strategies.NormalizationStrategy
-
Normalize a column, with a double value.
- NormalizedField - Class in org.encog.util.arrayutil
-
This object holds the normalization stats for a column.
- NormalizedField() - Constructor for class org.encog.util.arrayutil.NormalizedField
-
Construct the object with a range of 1 and -1.
- NormalizedField(double, double) - Constructor for class org.encog.util.arrayutil.NormalizedField
-
Construct the object.
- NormalizedField(NormalizationAction, String) - Constructor for class org.encog.util.arrayutil.NormalizedField
-
Construct an object.
- NormalizedField(NormalizationAction, String, double, double, double, double) - Constructor for class org.encog.util.arrayutil.NormalizedField
-
Construct the field, with no defaults.
- NormalizedField(String, NormalizationAction, double, double) - Constructor for class org.encog.util.arrayutil.NormalizedField
-
Construct the object.
- normalizedSize(ColumnDefinition, boolean) - Method in class org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
-
Calculate how many elements a column will normalize into.
- normalizedSize(ColumnDefinition, boolean) - Method in interface org.encog.ml.data.versatile.normalizers.strategies.NormalizationStrategy
-
Calculate how many elements a column will normalize into.
- normalizeInputColumn(int, String) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Normalize a single input column.
- normalizeInputVector(String[], double[], boolean) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Normalize a string array to an input vector.
- normalizeOutputColumn(int, String) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Normalize a single output column.
- Normalizer - Interface in org.encog.ml.data.versatile.normalizers
-
The normalizer interface defines how to normalize a column.
- NormalizeRange - Enum in org.encog.app.analyst.wizard
-
The normalization range that the Encog Analyst Wizard should use.
- normalizeToVector(ColumnDefinition, int, double[], boolean, String) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Normalize a single column to the input vector.
- notequ(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform a non-equal on two expressions.
- nr_class - Variable in class org.encog.mathutil.libsvm.svm_model
-
- nr_weight - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- nSV - Variable in class org.encog.mathutil.libsvm.svm_model
-
- nu - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- NU_SVC - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- NU_SVR - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- NullStatusReportable - Class in org.encog
-
A report object that does nothing.
- NullStatusReportable() - Constructor for class org.encog.NullStatusReportable
-
- NumberList - Class in org.encog.util.csv
-
Class used to handle lists of numbers.
- numClusters() - Method in class org.encog.ml.kmeans.KMeansClustering
-
- numClusters() - Method in interface org.encog.ml.MLClustering
-
- NumericDateUtil - Class in org.encog.util.time
-
- NumericDateUtil() - Constructor for class org.encog.util.time.NumericDateUtil
-
- NumericRange - Class in org.encog.mathutil
-
A numeric range has a high, low, mean, root-mean-square, standard deviation,
and the count of how many samples it contains.
- NumericRange(List<Double>) - Constructor for class org.encog.mathutil.NumericRange
-
Create a numeric range from a list of values.
- P - Static variable in class org.encog.engine.network.activation.ActivationLinear
-
Default empty parameters.
- p - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- para(String) - Method in class org.encog.util.HTMLReport
-
- ParallelScore - Class in org.encog.ml.ea.score.parallel
-
This class is used to calculate the scores for an entire population.
- ParallelScore(Population, GeneticCODEC, List<AdjustScore>, CalculateScore, int) - Constructor for class org.encog.ml.ea.score.parallel.ParallelScore
-
Construct the parallel score calculation object.
- ParallelScoreTask - Class in org.encog.ml.ea.score.parallel
-
An individual threadable task for the parallel score calculation.
- ParallelScoreTask(Genome, ParallelScore) - Constructor for class org.encog.ml.ea.score.parallel.ParallelScoreTask
-
Construct the parallel task.
- param - Variable in class org.encog.mathutil.libsvm.svm_model
-
- PARAM_C - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the const C.
- PARAM_CACHE_SIZE - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the cache size.
- PARAM_COEF0 - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the coef0.
- PARAM_COMPETITIVE_MAX_WINNERS - Static variable in class org.encog.engine.network.activation.ActivationCompetitive
-
The offset to the parameter that holds the max winners.
- PARAM_DEGREE - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the degree.
- PARAM_EPS - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the eps.
- PARAM_GAMMA - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the gamma.
- PARAM_KERNEL_TYPE - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the kernel type.
- PARAM_NU - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the nu.
- PARAM_NUM_WEIGHT - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the number of weights.
- PARAM_P - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the p.
- PARAM_PROBABILITY - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the probability.
- PARAM_RAMP_HIGH - Static variable in class org.encog.engine.network.activation.ActivationRamp
-
The ramp high parameter.
- PARAM_RAMP_HIGH_THRESHOLD - Static variable in class org.encog.engine.network.activation.ActivationRamp
-
The ramp high threshold parameter.
- PARAM_RAMP_LOW - Static variable in class org.encog.engine.network.activation.ActivationRamp
-
The ramp low parameter.
- PARAM_RAMP_LOW_THRESHOLD - Static variable in class org.encog.engine.network.activation.ActivationRamp
-
The ramp low threshold parameter.
- PARAM_SHRINKING - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the shrinking.
- PARAM_STEP_CENTER - Static variable in class org.encog.engine.network.activation.ActivationStep
-
The step center parameter.
- PARAM_STEP_HIGH - Static variable in class org.encog.engine.network.activation.ActivationStep
-
The step high parameter.
- PARAM_STEP_LOW - Static variable in class org.encog.engine.network.activation.ActivationStep
-
The step low parameter.
- PARAM_SVM_TYPE - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the SVM type.
- PARAM_WEIGHT - Static variable in class org.encog.ml.svm.PersistSVM
-
The paramater to hold the weight.
- PARAM_WEIGHT_LABEL - Static variable in class org.encog.ml.svm.PersistSVM
-
The parameter to hold the weight label.
- ParamsHolder - Class in org.encog.util
-
A class that can be used to parse parameters stored in a map.
- ParamsHolder(Map<String, String>, CSVFormat) - Constructor for class org.encog.util.ParamsHolder
-
Construct the object.
- ParamsHolder(Map<String, String>) - Constructor for class org.encog.util.ParamsHolder
-
Construct the object.
- ParamTemplate - Class in org.encog.ml.prg.extension
-
Provides a template for parameters to the opcodes.
- ParamTemplate() - Constructor for class org.encog.ml.prg.extension.ParamTemplate
-
Default constructor.
- parentsNeeded() - Method in class org.encog.ml.ea.opp.CompoundOperator
- parentsNeeded() - Method in interface org.encog.ml.ea.opp.EvolutionaryOperator
-
- parentsNeeded() - Method in class org.encog.ml.genetic.crossover.Splice
- parentsNeeded() - Method in class org.encog.ml.genetic.crossover.SpliceNoRepeat
- parentsNeeded() - Method in class org.encog.ml.genetic.mutate.MutatePerturb
- parentsNeeded() - Method in class org.encog.ml.genetic.mutate.MutateShuffle
- parentsNeeded() - Method in class org.encog.ml.prg.opp.ConstMutation
- parentsNeeded() - Method in class org.encog.ml.prg.opp.SubtreeCrossover
-
- parentsNeeded() - Method in class org.encog.ml.prg.opp.SubtreeMutation
-
- parentsNeeded() - Method in class org.encog.neural.neat.training.opp.NEATCrossover
- parentsNeeded() - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
- parse(String) - Method in class org.encog.ml.bayesian.parse.ParseProbability
-
Parse the given line.
- parse(String) - Method in class org.encog.parse.expression.common.ParseCommonExpression
-
- parse(String) - Method in class org.encog.parse.expression.epl.ParseEPL
-
- parse(String) - Method in class org.encog.util.csv.CSVFormat
-
Parse the specified string to a double.
- parse(String) - Method in class org.encog.util.csv.ParseCSVLine
-
- parse(String) - Static method in class org.encog.util.http.FormUtility
-
Parse a URL query string.
- parseActivationFunction(String) - Static method in class org.encog.persist.EncogFileSection
-
Parse an activation function from a value.
- parseActivationFunction(Map<String, String>, String) - Static method in class org.encog.persist.EncogFileSection
-
Parse an activation function from a string.
- parseAttributeName() - Method in class org.encog.parse.tags.read.ReadHTML
-
Parse the attribute name.
- parseAttributeName() - Method in class org.encog.parse.tags.read.ReadTags
-
Parse an attribute name, if one is present.
- parseBoolean(String) - Static method in class org.encog.ml.prg.EncogProgram
-
Parse the specified program, or expression, and return the result.
- parseBoolean(Map<String, String>, String) - Static method in class org.encog.persist.EncogFileSection
-
Parse a boolean from a name-value collection of params.
- ParseCommonExpression - Class in org.encog.parse.expression.common
-
This class is used to process a common format equation (in-fix) into the tree
format that Encog uses.
- ParseCommonExpression(EncogProgram) - Constructor for class org.encog.parse.expression.common.ParseCommonExpression
-
- ParseCSVLine - Class in org.encog.util.csv
-
- ParseCSVLine(CSVFormat) - Constructor for class org.encog.util.csv.ParseCSVLine
-
- parseDate(String) - Static method in class org.encog.bot.rss.RSS
-
Simple utility function that converts a RSS formatted date into a Java
date.
- parseDate(String) - Static method in class org.encog.util.csv.ReadCSV
-
Parse a date.
- ParsedChoice - Class in org.encog.ml.bayesian.parse
-
A parsed choice.
- ParsedChoice(String, double, double) - Constructor for class org.encog.ml.bayesian.parse.ParsedChoice
-
Construct a continuous choice, with a min and max.
- ParsedChoice(String, int) - Constructor for class org.encog.ml.bayesian.parse.ParsedChoice
-
Construct a discrete value for this choice.
- ParsedEvent - Class in org.encog.ml.bayesian.parse
-
A parsed event.
- ParsedEvent(String) - Constructor for class org.encog.ml.bayesian.parse.ParsedEvent
-
Construct a parsed even with the specified label.
- parseDouble(String) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Parse a double, using the correct formatter.
- parseDouble(Map<String, String>, String) - Static method in class org.encog.persist.EncogFileSection
-
Parse a double from a name-value collection of params.
- parseDoubleArray(Map<String, String>, String) - Method in class org.encog.persist.EncogFileSection
-
Parse a double array from a name-value collection of params.
- ParsedProbability - Class in org.encog.ml.bayesian.parse
-
A probability that has been parsed.
- ParsedProbability() - Constructor for class org.encog.ml.bayesian.parse.ParsedProbability
-
- ParseEPL - Class in org.encog.parse.expression.epl
-
Parse an EPL string.
- ParseEPL(EncogProgram) - Constructor for class org.encog.parse.expression.epl.ParseEPL
-
- ParseError - Exception in org.encog.parse
-
Indicates an error has occured in one of the parsers.
- ParseError(String) - Constructor for exception org.encog.parse.ParseError
-
Construct a message exception.
- ParseError(Throwable) - Constructor for exception org.encog.parse.ParseError
-
Construct an exception that holds another exception.
- parseExpression(String) - Static method in class org.encog.ml.prg.EncogProgram
-
Parse the specified program, or expression, and return the result.
- parseFloat(String) - Static method in class org.encog.ml.prg.EncogProgram
-
Parse the specified program, or expression, and return the result.
- parseInt(Map<String, String>, String) - Static method in class org.encog.persist.EncogFileSection
-
Parse an int from a name-value collection of params.
- parseIntArray(Map<String, String>, String) - Static method in class org.encog.persist.EncogFileSection
-
Parse an int array from a name-value collection of params.
- parseLayer(String, int) - Static method in class org.encog.ml.factory.parse.ArchitectureParse
-
parse a layer.
- parseLayers(String) - Static method in class org.encog.ml.factory.parse.ArchitectureParse
-
Parse all layers from a line of text.
- parseMatrix(Map<String, String>, String) - Static method in class org.encog.persist.EncogFileSection
-
Parse a matrix from a name-value collection of params.
- parseParams(String) - Static method in class org.encog.ml.factory.parse.ArchitectureParse
-
Parse parameters.
- parseParams() - Method in class org.encog.persist.EncogFileSection
-
- ParseProbability - Class in org.encog.ml.bayesian.parse
-
Used to parse probability strings for the Bayes networks.
- ParseProbability(BayesianNetwork) - Constructor for class org.encog.ml.bayesian.parse.ParseProbability
-
Parse the probability for the specified network.
- parseProbabilityList(BayesianNetwork, String) - Static method in class org.encog.ml.bayesian.parse.ParseProbability
-
Parse a probability list.
- parseString(String) - Static method in class org.encog.ml.prg.EncogProgram
-
Parse the specified program, or expression, and return the result.
- parseString() - Method in class org.encog.parse.tags.read.ReadTags
-
Called to parse a double or single quote string.
- parseTag() - Method in class org.encog.parse.tags.read.ReadTags
-
Called when a tag is detected.
- parseThroughComma() - Method in class org.encog.util.SimpleParser
-
- parseTimeSlice(String) - Static method in class org.encog.app.analyst.util.CSVHeaders
-
Parse a timeslice from a header such as (t-1).
- passInit() - Method in class org.encog.util.normalize.segregate.index.IndexSegregator
-
Reset the counter to zero.
- passInit() - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
Init for a new pass.
- passInit() - Method in class org.encog.util.normalize.segregate.RangeSegregator
-
Nothing needs to be done to setup for a pass.
- passInit() - Method in interface org.encog.util.normalize.segregate.Segregator
-
Init for a pass.
- PassThroughNormalizer - Class in org.encog.ml.data.versatile.normalizers
-
A normalizer that simply passes the value through unnormalized.
- PassThroughNormalizer() - Constructor for class org.encog.ml.data.versatile.normalizers.PassThroughNormalizer
-
- PatternError - Exception in org.encog.neural.pattern
-
This class is thrown when an error occurs while using one of the neural
network pattern classes.
- PatternError(String) - Constructor for exception org.encog.neural.pattern.PatternError
-
Construct a message exception.
- PatternError(Throwable) - Constructor for exception org.encog.neural.pattern.PatternError
-
Construct an exception that holds another exception.
- pause() - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
Pause the training to continue later.
- pause() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Pause the training to continue later.
- pause() - Method in class org.encog.ml.fitting.gaussian.TrainGaussian
-
- pause() - Method in class org.encog.ml.fitting.linear.TrainLinearRegression
-
- pause() - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
Pause the training to continue later.
- pause() - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- pause() - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- pause() - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
Pause the training to continue later.
- pause() - Method in class org.encog.ml.svm.training.SVMTrain
-
Pause the training to continue later.
- pause() - Method in interface org.encog.ml.train.MLTrain
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.cpn.training.TrainInstar
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.cpn.training.TrainOutstar
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.freeform.training.FreeformBackPropagation
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
- pause() - Method in class org.encog.neural.networks.training.cross.CrossValidationKFold
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.networks.training.nm.NelderMeadTraining
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
Pause the training.
- pause() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
This training type does not support training continue.
- pause() - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
Pause the training.
- pause() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Pause the training.
- pause() - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
This training type does not support training continue.
- pause() - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
- pause() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.rbf.training.SVDTraining
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Pause the training to continue later.
- pause() - Method in class org.encog.neural.som.training.clustercopy.SOMClusterCopyTraining
-
Pause the training to continue later.
- peek() - Method in class org.encog.parse.PeekableInputStream
-
Peek at the next character from the stream.
- peek(int) - Method in class org.encog.parse.PeekableInputStream
-
Peek at a specified depth.
- peek(String) - Method in class org.encog.parse.PeekableInputStream
-
Peek ahead and see if the specified string is present.
- peek() - Method in class org.encog.util.datastruct.StackObject
-
- peek() - Method in class org.encog.util.SimpleParser
-
- PeekableInputStream - Class in org.encog.parse
-
This is a special input stream that allows the program to peek one or more
characters ahead in the file.
- PeekableInputStream(InputStream) - Constructor for class org.encog.parse.PeekableInputStream
-
The constructor accepts an InputStream to setup the object.
- perform(List<DataDivision>, VersatileMLDataSet, int, int) - Method in class org.encog.ml.data.versatile.division.PerformDataDivision
-
Perform the split.
- perform(World, State, Action) - Method in interface org.encog.ml.world.PerformAction
-
- perform(TrainingJob) - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer
-
Perform the specified job.
- perform(TrainingJob) - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
-
Perform the specified job.
- PerformAction - Interface in org.encog.ml.world
-
- PerformAnalysis - Class in org.encog.app.analyst.analyze
-
This class is used to perform an analysis of a CSV file.
- PerformAnalysis(AnalystScript, String, boolean, AnalystFileFormat) - Constructor for class org.encog.app.analyst.analyze.PerformAnalysis
-
Construct the analysis object.
- performAntiSelection(Random, Species) - Method in interface org.encog.ml.ea.opp.selection.SelectionOperator
-
Selects an unfit genome.
- performAntiSelection(Random, Species) - Method in class org.encog.ml.ea.opp.selection.TournamentSelection
-
Selects an unfit genome.
- performAntiSelection(Random, Species) - Method in class org.encog.ml.ea.opp.selection.TruncationSelection
-
Selects an unfit genome.
- performBasicCounts() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Perform a basic analyze of the file.
- performCalculation() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Perform the internal calculation for this neuron.
- performCalculation() - Method in interface org.encog.neural.freeform.FreeformNeuron
-
Perform the internal calculation for this neuron.
- performConnectionTask(ConnectionTask) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Perform the specified connection task.
- PerformDataDivision - Class in org.encog.ml.data.versatile.division
-
Perform a data division.
- PerformDataDivision(boolean, GenerateRandom) - Constructor for class org.encog.ml.data.versatile.division.PerformDataDivision
-
Construct the data division processor.
- PerformerTask - Class in org.encog.neural.networks.training.concurrent.performers
-
A task to be performed.
- PerformerTask(ConcurrentTrainingPerformer) - Constructor for class org.encog.neural.networks.training.concurrent.performers.PerformerTask
-
Construct the object.
- performJobUnit(JobUnitContext) - Method in class org.encog.neural.prune.PruneIncremental
-
Perform an individual job unit, which is a single network to train and
evaluate.
- performJobUnit(JobUnitContext) - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
Perform one job unit.
- performNeuronTask(NeuronTask) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Perform the specified neuron task.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.ea.opp.CompoundOperator
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in interface org.encog.ml.ea.opp.EvolutionaryOperator
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.genetic.crossover.Splice
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.genetic.crossover.SpliceNoRepeat
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.genetic.mutate.MutatePerturb
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.genetic.mutate.MutateShuffle
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.prg.opp.ConstMutation
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.prg.opp.SubtreeCrossover
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.ml.prg.opp.SubtreeMutation
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.neural.neat.training.opp.NEATCrossover
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.neural.neat.training.opp.NEATMutateAddLink
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.neural.neat.training.opp.NEATMutateAddNode
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.neural.neat.training.opp.NEATMutateRemoveLink
-
Perform the evolutionary operation.
- performOperation(Random, Genome[], int, Genome[], int) - Method in class org.encog.neural.neat.training.opp.NEATMutateWeights
-
Perform the evolutionary operation.
- performQuery(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Perform a query.
- performRevert(Map<String, String>) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Perform a revert.
- performSelection(Random, Species) - Method in interface org.encog.ml.ea.opp.selection.SelectionOperator
-
Selects an fit genome.
- performSelection(Random, Species) - Method in class org.encog.ml.ea.opp.selection.TournamentSelection
-
Selects an fit genome.
- performSelection(Random, Species) - Method in class org.encog.ml.ea.opp.selection.TruncationSelection
-
Selects an fit genome.
- performShutdownTask() - Method in interface org.encog.EncogShutdownTask
-
- performShutdownTask() - Method in class org.encog.ml.ea.train.basic.BasicEA
- performSpeciation(List<Genome>) - Method in class org.encog.ml.ea.species.SingleSpeciation
-
Perform the speciation.
- performSpeciation(List<Genome>) - Method in interface org.encog.ml.ea.species.Speciation
-
Perform the speciation.
- performSpeciation(List<Genome>) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
Perform the speciation.
- PersistART1 - Class in org.encog.neural.art
-
Persist an ART1 network.
- PersistART1() - Constructor for class org.encog.neural.art.PersistART1
-
- PersistBAM - Class in org.encog.neural.bam
-
Persist the BAM network.
- PersistBAM() - Constructor for class org.encog.neural.bam.PersistBAM
-
- PersistBasicNetwork - Class in org.encog.neural.networks
-
Persist a basic network.
- PersistBasicNetwork() - Constructor for class org.encog.neural.networks.PersistBasicNetwork
-
- PersistBasicPNN - Class in org.encog.neural.pnn
-
Persist a PNN.
- PersistBasicPNN() - Constructor for class org.encog.neural.pnn.PersistBasicPNN
-
- PersistBasicUniverse - Class in org.encog.ca.universe.basic
-
- PersistBasicUniverse() - Constructor for class org.encog.ca.universe.basic.PersistBasicUniverse
-
- PersistBayes - Class in org.encog.ml.bayesian
-
Persist a Bayesian network.
- PersistBayes() - Constructor for class org.encog.ml.bayesian.PersistBayes
-
- PersistBoltzmann - Class in org.encog.neural.thermal
-
Persist the Boltzmann machine.
- PersistBoltzmann() - Constructor for class org.encog.neural.thermal.PersistBoltzmann
-
- PersistConst - Class in org.encog.persist
-
Some common persistance constants.
- PersistCPN - Class in org.encog.neural.cpn
-
Persist a CPN network.
- PersistCPN() - Constructor for class org.encog.neural.cpn.PersistCPN
-
- PersistError - Exception in org.encog.persist
-
General error class for Encog persistence.
- PersistError(String) - Constructor for exception org.encog.persist.PersistError
-
Construct a message exception.
- PersistError(String, Throwable) - Constructor for exception org.encog.persist.PersistError
-
Construct an exception that holds another exception.
- PersistError(Throwable) - Constructor for exception org.encog.persist.PersistError
-
Construct an exception that holds another exception.
- PersistHMM - Class in org.encog.ml.hmm
-
Persist a HMM.
- PersistHMM() - Constructor for class org.encog.ml.hmm.PersistHMM
-
- PersistHopfield - Class in org.encog.neural.thermal
-
Persist the Hopfield network.
- PersistHopfield() - Constructor for class org.encog.neural.thermal.PersistHopfield
-
- PersistNEATPopulation - Class in org.encog.neural.neat
-
Persist a NEAT or HyperNEAT network.
- PersistNEATPopulation() - Constructor for class org.encog.neural.neat.PersistNEATPopulation
-
- PersistorRegistry - Class in org.encog.persist
-
Registry to hold persistors.
- PersistPrgPopulation - Class in org.encog.ml.prg
-
Persist the Encog population.
- PersistPrgPopulation() - Constructor for class org.encog.ml.prg.PersistPrgPopulation
-
- PersistRBFNetwork - Class in org.encog.neural.rbf
-
Persist a RBF network.
- PersistRBFNetwork() - Constructor for class org.encog.neural.rbf.PersistRBFNetwork
-
- PersistSOM - Class in org.encog.neural.som
-
Persist the SOM.
- PersistSOM() - Constructor for class org.encog.neural.som.PersistSOM
-
- PersistSVM - Class in org.encog.ml.svm
-
Persist a SVM.
- PersistSVM() - Constructor for class org.encog.ml.svm.PersistSVM
-
- PersistTrainingContinuation - Class in org.encog.neural.networks.training.propagation
-
Persist the training continuation.
- PersistTrainingContinuation() - Constructor for class org.encog.neural.networks.training.propagation.PersistTrainingContinuation
-
- pick(Random) - Method in class org.encog.util.obj.ChooseObject
-
Choose a random object.
- pickFirst() - Method in class org.encog.util.obj.ChooseObject
-
- pickMaxParents(Random, int) - Method in class org.encog.ml.ea.opp.OperationList
-
Pick a operator based on the number of parents available.
- plural(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames
-
Get the plural form for a TimeUnit.
- plural(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames
-
Get the plural name for the specified time unit.
- plus(ComplexNumber) - Method in class org.encog.mathutil.ComplexNumber
-
Addition of Complex numbers (doesn't change this Complex number).
- plus(MLData) - Method in class org.encog.ml.data.basic.BasicMLData
-
Add one data element to another.
- PNNConfig - Class in org.encog.ml.model.config
-
Config class for EncogModel to use a PNN neural network.
- PNNConfig() - Constructor for class org.encog.ml.model.config.PNNConfig
-
- PNNFactory - Class in org.encog.ml.factory.method
-
A factory to create PNN networks.
- PNNFactory() - Constructor for class org.encog.ml.factory.method.PNNFactory
-
- PNNKernelType - Enum in org.encog.neural.pnn
-
Specifies the kernel type for the PNN.
- PNNOutputMode - Enum in org.encog.neural.pnn
-
The output mode that will be used by the PNN.
- PNNPattern - Class in org.encog.neural.pattern
-
Pattern to create a PNN.
- PNNPattern() - Constructor for class org.encog.neural.pattern.PNNPattern
-
- PNNTrainFactory - Class in org.encog.ml.factory.train
-
A factory used to create PNN trainers.
- PNNTrainFactory() - Constructor for class org.encog.ml.factory.train.PNNTrainFactory
-
- POLY - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- PoolItem - Class in org.encog.util.concurrency
-
An Encog task being executed by the Java thread pool.
- PoolItem(EngineTask, TaskGroup) - Constructor for class org.encog.util.concurrency.PoolItem
-
Create a pool item.
- pop() - Method in class org.encog.app.quant.util.BarBuffer
-
Pop (and remove) the oldest bar in the buffer.
- pop() - Method in class org.encog.ml.graph.search.FrontierHolder
-
- pop() - Method in class org.encog.util.datastruct.StackInt
-
- pop() - Method in class org.encog.util.datastruct.StackObject
-
- pop() - Method in class org.encog.util.datastruct.StackString
-
- Population - Interface in org.encog.ml.ea.population
-
Defines a population of genomes.
- PopulationGenerator - Interface in org.encog.ml.ea.population
-
Generate a random population.
- POSITIVE_ETA - Static variable in class org.encog.neural.networks.training.propagation.resilient.RPROPConst
-
The POSITIVE ETA value.
- postIteration() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Call the strategies after an iteration.
- postIteration() - Method in class org.encog.ml.train.BasicTraining
-
Call the strategies after an iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.end.EndIterationsStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.end.EndMaxErrorStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.end.EndMinutesStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.Greedy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.HybridStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.RequiredImprovementStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.ResetStrategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.ml.train.strategy.StopTrainingStrategy
-
Called just after a training iteration.
- postIteration() - Method in interface org.encog.ml.train.strategy.Strategy
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Call the strategies after an iteration.
- postIteration() - Method in class org.encog.neural.networks.training.strategy.RegularizationStrategy
-
- postIteration() - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate
-
Called just after a training iteration.
- postIteration() - Method in class org.encog.neural.networks.training.strategy.SmartMomentum
-
Called just after a training iteration.
- pow(double, double) - Static method in class org.encog.mathutil.BoundMath
-
Calculate the power of a number.
- pow(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform a protected div on two expression values.
- PRECOMPUTED - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- PredictionType - Enum in org.encog.app.analyst.wizard
-
- preIteration() - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Call the strategies before an iteration.
- preIteration() - Method in class org.encog.ml.train.BasicTraining
-
Call the strategies before an iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.end.EndIterationsStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.end.EndMaxErrorStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.end.EndMinutesStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.Greedy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.HybridStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.RequiredImprovementStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.ResetStrategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.ml.train.strategy.StopTrainingStrategy
-
Called just before a training iteration.
- preIteration() - Method in interface org.encog.ml.train.strategy.Strategy
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.neural.networks.training.strategy.RegularizationStrategy
-
- preIteration() - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate
-
Called just before a training iteration.
- preIteration() - Method in class org.encog.neural.networks.training.strategy.SmartMomentum
-
Called just before a training iteration.
- prepareOutputFile(File) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Prepare the output file, write headers if needed.
- prepareOutputFile(File) - Method in class org.encog.app.analyst.csv.process.AnalystProcess
-
Prepare the output file, write headers if needed.
- prepareRead() - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
Prepare to read from an external data source.
- prepareRead() - Method in class org.encog.ml.data.buffer.codec.CSVDataCODEC
-
Prepare to read from the CSV file.
- prepareRead() - Method in interface org.encog.ml.data.buffer.codec.DataSetCODEC
-
Prepare to read from an external data source.
- prepareRead() - Method in class org.encog.ml.data.buffer.codec.ExcelCODEC
-
Prepare to read from an external data source.
- prepareRead() - Method in class org.encog.ml.data.buffer.codec.NeuralDataSetCODEC
-
Prepare to read from an external data source.
- prepareRead() - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
-
Prepare to read from an external data source.
- prepareRevert() - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Prepare a revert.
- prepareWrite(int, int, int) - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
Prepare to write to an external data destination.
- prepareWrite(int, int, int) - Method in class org.encog.ml.data.buffer.codec.CSVDataCODEC
-
Prepare to write to a CSV file.
- prepareWrite(int, int, int) - Method in interface org.encog.ml.data.buffer.codec.DataSetCODEC
-
Prepare to write to an external data destination.
- prepareWrite(int, int, int) - Method in class org.encog.ml.data.buffer.codec.ExcelCODEC
-
Prepare to write to an external data destination.
- prepareWrite(int, int, int) - Method in class org.encog.ml.data.buffer.codec.NeuralDataSetCODEC
-
Prepare to write to an external data destination.
- prepareWrite(int, int, int) - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
-
Prepare to write to an external data destination.
- PreprocessAction - Enum in org.encog.app.analyst.script.preprocess
-
- PrgCODEC - Class in org.encog.ml.prg
-
Encode and decode an Encog program between genome and phenotypes.
- PrgCODEC() - Constructor for class org.encog.ml.prg.PrgCODEC
-
- PrgFullGenerator - Class in org.encog.ml.prg.generator
-
The full generator works by creating program trees that do not stop
prematurely.
- PrgFullGenerator(EncogProgramContext, int) - Constructor for class org.encog.ml.prg.generator.PrgFullGenerator
-
Construct the full generator.
- PrgGenerator - Interface in org.encog.ml.prg.generator
-
Generate a random Encog Program.
- PrgGenomeFactory - Class in org.encog.ml.prg.train
-
A GenomeFactory that creates EncogProgram genomes.
- PrgGenomeFactory(EncogProgramContext) - Constructor for class org.encog.ml.prg.train.PrgGenomeFactory
-
Construct a factory.
- PrgGrowGenerator - Class in org.encog.ml.prg.generator
-
The grow generator creates a random program by choosing a random node from
both the "function and terminal" sets until the maximum depth is reached.
- PrgGrowGenerator(EncogProgramContext, int) - Constructor for class org.encog.ml.prg.generator.PrgGrowGenerator
-
Construct the grow generator.
- PrgPopulation - Class in org.encog.ml.prg.train
-
A population that contains EncogProgram's.
- PrgPopulation(EncogProgramContext, int) - Constructor for class org.encog.ml.prg.train.PrgPopulation
-
Construct the population.
- PrgSpeciation - Class in org.encog.ml.prg.species
-
Perform speciation for two Encog programs.
- PrgSpeciation() - Constructor for class org.encog.ml.prg.species.PrgSpeciation
-
- print(String) - Method in interface org.encog.mathutil.libsvm.svm_print_interface
-
- Prioritizer - Interface in org.encog.ml.graph.search
-
- probA - Variable in class org.encog.mathutil.libsvm.svm_model
-
- probability - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- probability - Variable in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
Probability.
- probability() - Method in class org.encog.ml.hmm.alog.ForwardBackwardCalculator
-
- probability(MLDataPair) - Method in class org.encog.ml.hmm.distributions.ContinousDistribution
-
Determine the probability of the specified data pair.
- probability(MLDataPair) - Method in class org.encog.ml.hmm.distributions.DiscreteDistribution
-
Determine the probability of the specified data pair.
- probability(MLDataPair) - Method in interface org.encog.ml.hmm.distributions.StateDistribution
-
Determine the probability of the specified data pair.
- probability(MLDataSet) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- probability(MLDataSet, int[]) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- probability(MLDataSet) - Method in interface org.encog.ml.MLStateSequence
-
Determine the probability of the specified sequence.
- probability(MLDataSet, int[]) - Method in interface org.encog.ml.MLStateSequence
-
Determine the probability for the specified sequence and states.
- probability(String) - Method in class org.encog.util.text.BagOfWords
-
- probB - Variable in class org.encog.mathutil.libsvm.svm_model
-
- process(EncogAnalyst) - Method in class org.encog.app.analyst.analyze.PerformAnalysis
-
Perform the analysis.
- process(File, int, EncogAnalyst, int) - Method in class org.encog.app.analyst.csv.AnalystClusterCSV
-
Process the file and cluster.
- process(File, MLMethod) - Method in class org.encog.app.analyst.csv.AnalystEvaluateCSV
-
Process the file.
- process(File, MLRegression) - Method in class org.encog.app.analyst.csv.AnalystEvaluateRawCSV
-
Process the file.
- process(File, int, int) - Method in class org.encog.app.analyst.csv.balance.BalanceCSV
-
Process and balance the data.
- process(File) - Method in class org.encog.app.analyst.csv.filter.FilterCSV
-
Process the input file.
- process(File) - Method in class org.encog.app.analyst.csv.process.AnalystProcess
-
Process, and generate the output file.
- process() - Method in class org.encog.app.analyst.csv.segregate.SegregateCSV
-
Process the input file and segregate into the output files.
- process(File) - Method in class org.encog.app.analyst.csv.shuffle.ShuffleCSV
-
Process, and generate the output file.
- process(File, File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.sort.SortCSV
-
Process, and sort the files.
- process(double[]) - Method in class org.encog.app.analyst.csv.TimeSeriesUtil
-
Process a row.
- process(File) - Method in class org.encog.app.quant.indicators.ProcessIndicators
-
Process and write the specified output file.
- process(File) - Method in class org.encog.app.quant.ninja.NinjaFileConvert
-
Process the file and output to the target file.
- process(boolean) - Method in class org.encog.ml.data.cross.KFoldCrossvalidation
-
- process() - Method in class org.encog.ml.ea.score.parallel.ParallelScore
-
Calculate the scores.
- process(TreeNode) - Static method in class org.encog.ml.tree.traverse.tasks.TaskCountNodes
-
Count the nodes from this tree node.
- process(int, TreeNode) - Static method in class org.encog.ml.tree.traverse.tasks.TaskGetNodeIndex
-
Obtain the specified tree node for the specified index.
- process(TreeNode, TreeNode, TreeNode) - Static method in class org.encog.ml.tree.traverse.tasks.TaskReplaceNode
-
Replace one node with another.
- process() - Method in class org.encog.neural.prune.PruneIncremental
-
Begin the prune process.
- process(double[]) - Method in class org.encog.util.arrayutil.NormalizeArray
-
Normalize the array.
- process(double[]) - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
Process the array.
- process(double[][]) - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
Processes the specified data array in an IMLDataset.
- process() - Method in class org.encog.util.benchmark.EncogBenchmark
-
Perform the benchmark.
- process() - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
Process the job.
- process() - Method in class org.encog.util.kmeans.KMeansUtil
-
Perform the cluster.
- process() - Method in class org.encog.util.normalize.DataNormalization
-
Call this method to begin the normalization process.
- process(String) - Method in class org.encog.util.text.BagOfWords
-
- PROCESS_CONFIG_BACKWARD_SIZE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "PROCESS:CONFIG,backwardSize".
- PROCESS_CONFIG_FORWARD_SIZE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "PROCESS:CONFIG,forwardSize".
- PROCESS_CONFIG_SOURCE_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "PROCESS:CONFIG,sourceFile".
- PROCESS_CONFIG_TARGET_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "PROCESS:CONFIG,targetFile".
- processBackground() - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
- processBatches() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Process training batches.
- processCell(int, int) - Method in class org.encog.ca.program.conway.ConwayProgram
-
- processCell(int, int) - Method in class org.encog.ca.program.generic.GenericCA
-
- processDouble(ColumnDefinition) - Method in class org.encog.ml.data.versatile.missing.MeanMissingHandler
- processDouble(ColumnDefinition) - Method in interface org.encog.ml.data.versatile.missing.MissingHandler
-
- ProcessExtension - Class in org.encog.app.analyst.csv.process
-
- ProcessExtension(CSVFormat) - Constructor for class org.encog.app.analyst.csv.process.ProcessExtension
-
- ProcessField - Class in org.encog.app.analyst.script.process
-
Holds one field for Encog analyst preprocess.
- ProcessField(String, String) - Constructor for class org.encog.app.analyst.script.process.ProcessField
-
Construct this field.
- processImage(Image) - Method in interface org.encog.util.downsample.Downsample
-
Process the specified image.
- processImage(Image) - Method in class org.encog.util.downsample.RGBDownsample
-
Process the image and prepare it to be downsampled.
- ProcessIndicators - Class in org.encog.app.quant.indicators
-
Process indicators and generate output.
- ProcessIndicators() - Constructor for class org.encog.app.quant.indicators.ProcessIndicators
-
- processPureBatch() - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Process training for pure batch mode (one single batch).
- processString(ColumnDefinition) - Method in class org.encog.ml.data.versatile.missing.MeanMissingHandler
-
Process a column's missing data.
- processString(ColumnDefinition) - Method in interface org.encog.ml.data.versatile.missing.MissingHandler
-
Process a column's missing data.
- processTask(EngineTask) - Method in class org.encog.util.concurrency.EngineConcurrency
-
Process the specified task.
- processTask(EngineTask, TaskGroup) - Method in class org.encog.util.concurrency.EngineConcurrency
-
Process the specified task.
- processToken(String) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Process the specified token.
- processToken(String) - Method in class org.encog.app.generate.generators.mql4.GenerateMQL4
-
- processToken(String) - Method in class org.encog.app.generate.generators.ninja.GenerateNinjaScript
-
- processToPair(double[]) - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
Process the data array and returns an MLdatapair.
- produceKeyLink(long, long) - Static method in class org.encog.neural.neat.training.NEATInnovationList
-
Produce a key for a link.
- produceKeyNeuron(long) - Static method in class org.encog.neural.neat.training.NEATInnovationList
-
Produce an innovation key for a neuron.
- produceKeyNeuronSplit(long, long) - Static method in class org.encog.neural.neat.training.NEATInnovationList
-
Produce a key for a split neuron.
- produceReport() - Method in class org.encog.app.analyst.report.AnalystReport
-
Produce the report.
- produceReport(File) - Method in class org.encog.app.analyst.report.AnalystReport
-
Produce a report for a filename.
- ProgramExtensionTemplate - Interface in org.encog.ml.prg.extension
-
Defines an opcode.
- ProgramGenerator - Interface in org.encog.app.generate.generators
-
This interface defines a generator that works from program blocks, rather
than a template.
- ProgramNode - Class in org.encog.ml.prg
-
Represents a program node in an EPL program.
- ProgramNode(EncogProgram, ProgramExtensionTemplate, ProgramNode[]) - Constructor for class org.encog.ml.prg.ProgramNode
-
Construct the program node.
- Propagation - Class in org.encog.neural.networks.training.propagation
-
Implements basic functionality that is needed by each of the propagation
methods.
- Propagation(ContainsFlat, MLDataSet) - Constructor for class org.encog.neural.networks.training.propagation.Propagation
-
Construct a propagation object.
- PROPERTIES - Static variable in class org.encog.persist.PersistConst
-
Properties.
- PROPERTY_A1 - Static variable in class org.encog.neural.art.ART
-
Neural network property, the A1 parameter.
- PROPERTY_AF - Static variable in class org.encog.ml.factory.MLMethodFactory
-
- PROPERTY_B1 - Static variable in class org.encog.neural.art.ART
-
Neural network property, the B1 parameter.
- PROPERTY_BAYESIAN_REGULARIZATION - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for bayes reg.
- PROPERTY_C - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for constant.
- PROPERTY_C1 - Static variable in class org.encog.ml.factory.train.SVMSearchFactory
-
Property for constant.
- PROPERTY_C1 - Static variable in class org.encog.neural.art.ART
-
Neural network property, the C1 parameter.
- PROPERTY_C2 - Static variable in class org.encog.ml.factory.train.SVMSearchFactory
-
Property for constant.
- PROPERTY_C_STEP - Static variable in class org.encog.ml.factory.train.SVMSearchFactory
-
Property for constant.
- PROPERTY_CYCLES - Static variable in class org.encog.ml.factory.MLMethodFactory
-
- PROPERTY_CYCLES - Static variable in class org.encog.neural.neat.NEATPopulation
-
Property to hold the number of cycles.
- PROPERTY_D1 - Static variable in class org.encog.neural.art.ART
-
Neural network property, the D1 parameter.
- PROPERTY_DIMENSIONS - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for dimensions.
- PROPERTY_END_LEARNING_RATE - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for ending learning rate.
- PROPERTY_END_RADIUS - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for ending radius.
- PROPERTY_F1_COUNT - Static variable in class org.encog.persist.PersistConst
-
The F1 count.
- PROPERTY_F2_COUNT - Static variable in class org.encog.persist.PersistConst
-
The F2 count.
- PROPERTY_GAMMA - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for gamma.
- PROPERTY_GAMMA1 - Static variable in class org.encog.ml.factory.train.SVMSearchFactory
-
Property for gamma.
- PROPERTY_GAMMA2 - Static variable in class org.encog.ml.factory.train.SVMSearchFactory
-
Property for gamma.
- PROPERTY_GAMMA_STEP - Static variable in class org.encog.ml.factory.train.SVMSearchFactory
-
Property for gamma.
- PROPERTY_ID - Static variable in class org.encog.persist.PersistConst
-
Property id.
- PROPERTY_INITIAL_UPDATE - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for init update.
- PROPERTY_ITERATIONS - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for iterations.
- PROPERTY_L - Static variable in class org.encog.neural.art.ART
-
Neural network property, the L parameter.
- PROPERTY_LEARNING_MOMENTUM - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for momentum.
- PROPERTY_LEARNING_RATE - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for learning rate.
- PROPERTY_MAX_PARENTS - Static variable in class org.encog.ml.factory.MLTrainFactory
-
- PROPERTY_MAX_STEP - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for max step.
- PROPERTY_NEAT_ACTIVATION - Static variable in class org.encog.neural.neat.NEATPopulation
-
The activation function to use.
- PROPERTY_NEIGHBORHOOD - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for neighborhood.
- PROPERTY_NO_WINNER - Static variable in class org.encog.neural.art.ART
-
Neural network property for no winner.
- PROPERTY_outputMode - Static variable in class org.encog.neural.pnn.PersistBasicPNN
-
The output mode property.
- PROPERTY_PARTICLES - Static variable in class org.encog.ml.factory.MLTrainFactory
-
- PROPERTY_POPULATION_SIZE - Static variable in class org.encog.ml.factory.MLMethodFactory
-
Population size.
- PROPERTY_POPULATION_SIZE - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Population size.
- PROPERTY_POPULATION_SIZE - Static variable in class org.encog.neural.neat.NEATPopulation
-
Property tag for the population size.
- PROPERTY_PROPERTY_NEIGHBORHOOD - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for neighborhood.
- PROPERTY_RBF_TYPE - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for rbf type.
- PROPERTY_START_LEARNING_RATE - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for starting learning rate.
- PROPERTY_START_RADIUS - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Property for starting radius.
- PROPERTY_SURVIVAL_RATE - Static variable in class org.encog.neural.neat.NEATPopulation
-
Property tag for the survival rate.
- PROPERTY_TEMPERATURE_START - Static variable in class org.encog.ml.factory.MLTrainFactory
-
The starting temperature.
- PROPERTY_TEMPERATURE_STOP - Static variable in class org.encog.ml.factory.MLTrainFactory
-
The ending temperature.
- PROPERTY_VIGILANCE - Static variable in class org.encog.neural.art.ART
-
Neural network property, the vigilance parameter.
- PROPERTY_WEIGHTS_F1_F2 - Static variable in class org.encog.persist.PersistConst
-
The weights from F1 to F2.
- PROPERTY_WEIGHTS_F2_F1 - Static variable in class org.encog.persist.PersistConst
-
The weights from F2 to F1.
- PropertyConstraints - Class in org.encog.app.analyst.script.prop
-
Holds constant type information for each of the properties that the script
might have.
- PropertyEntry - Class in org.encog.app.analyst.script.prop
-
A property entry for the Encog Analyst.
- PropertyEntry(PropertyType, String, String) - Constructor for class org.encog.app.analyst.script.prop.PropertyEntry
-
Construct a property entry.
- PropertyType - Enum in org.encog.app.analyst.script.prop
-
The property types supported for Encog Analyst.
- protectedDiv(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform a protected div on two expression values.
- prune(int, int) - Method in class org.encog.neural.prune.PruneSelective
-
Prune one of the neurons from this layer.
- PruneIncremental - Class in org.encog.neural.prune
-
This class is used to help determine the optimal configuration for the hidden
layers of a neural network.
- PruneIncremental(MLDataSet, NeuralNetworkPattern, int, int, int, StatusReportable) - Constructor for class org.encog.neural.prune.PruneIncremental
-
Construct an object to determine the optimal number of hidden layers and
neurons for the specified training data and pattern.
- PruneSelective - Class in org.encog.neural.prune
-
Prune a neural network selectively.
- PruneSelective(BasicNetwork) - Constructor for class org.encog.neural.prune.PruneSelective
-
Construct an object prune the neural network.
- PSOFactory - Class in org.encog.ml.factory.train
-
A factory for quick propagation training.
- PSOFactory() - Constructor for class org.encog.ml.factory.train.PSOFactory
-
- purge() - Method in class org.encog.ml.ea.species.BasicSpecies
-
Purge all members, increase age by one and count the number of
generations with no improvement.
- purgeInvalidGenomes() - Method in class org.encog.ml.ea.population.BasicPopulation
-
Purge any invalid genomes.
- purgeInvalidGenomes() - Method in interface org.encog.ml.ea.population.Population
-
Purge any invalid genomes.
- push(int) - Method in class org.encog.util.datastruct.StackInt
-
Push an int onto the stack.
- push(T) - Method in class org.encog.util.datastruct.StackObject
-
- push(String) - Method in class org.encog.util.datastruct.StackString
-
- put(MLDataPair, int) - Method in class org.encog.ml.hmm.train.kmeans.Clusters
-
- put(String, double[]) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
-
Save a list of doubles.
- putArray(UNIT_TYPE[]) - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Store the array.
- putArray(double[]) - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
Convert an array of doubles to the current best network.
- putArray(Double[]) - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper
-
Used to pass the putArray call on to the parent object.
- pythag(double, double) - Static method in class org.encog.neural.rbf.training.SVD
-
- rad2deg(double) - Static method in class org.encog.mathutil.EncogMath
-
Convert radians to degrees.
- RadialBasisFunction - Interface in org.encog.mathutil.rbf
-
A multi-dimension RBF.
- RadialBasisPattern - Class in org.encog.neural.pattern
-
A radial basis function (RBF) network uses several radial basis functions to
provide a more dynamic hidden layer activation function than many other types
of neural network.
- RadialBasisPattern() - Constructor for class org.encog.neural.pattern.RadialBasisPattern
-
- RampedHalfAndHalf - Class in org.encog.ml.prg.generator
-
Because neither the grow or full method provide a very wide array of sizes or
shapes on their own, Koza (1992) proposed a combination called ramped
half-and-half.
- RampedHalfAndHalf(EncogProgramContext, int, int) - Constructor for class org.encog.ml.prg.generator.RampedHalfAndHalf
-
Construct the ramped half-and-half generator.
- rand - Static variable in class org.encog.mathutil.libsvm.svm
-
- RANDOM_LENGTH - Static variable in class org.encog.util.http.FormUtility
-
The length of random string to create for multipart.
- RandomChoice - Class in org.encog.mathutil.randomize
-
Generate random choices unevenly.
- RandomChoice(double[]) - Constructor for class org.encog.mathutil.randomize.RandomChoice
-
Construct a list of probabilities.
- RandomFactory - Interface in org.encog.mathutil.randomize.factory
-
- randomInt(int, int) - Static method in class org.encog.mathutil.randomize.RangeRandomizer
-
Returns a random number in the range between min and max.
- randomise(double[]) - Method in class org.encog.mathutil.VectorAlgebra
-
v = U(0, 0.1)
- randomise(double[], double) - Method in class org.encog.mathutil.VectorAlgebra
-
v = U(-1, 1) * maxValue
Randomise each component of a vector to
[-maxValue, maxValue].
- randomize() - Method in interface org.encog.ca.program.CAProgram
-
- randomize() - Method in class org.encog.ca.program.conway.ConwayProgram
-
- randomize() - Method in class org.encog.ca.program.elementary.ElementaryCA
-
- randomize() - Method in class org.encog.ca.program.generic.GenericCA
-
- randomize() - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- randomize() - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- randomize() - Method in class org.encog.ca.universe.basic.BasicUniverse
-
- randomize() - Method in interface org.encog.ca.universe.Universe
-
- randomize() - Method in interface org.encog.ca.universe.UniverseCell
-
- randomize(double, double) - Method in class org.encog.mathutil.matrices.Matrix
-
Randomize the matrix.
- randomize(BasicNetwork, int) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
Randomize one level of a neural network.
- randomize(double[]) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
Randomize the array based on an array, modify the array.
- randomize(double[], int, int) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
Randomize the array based on an array, modify the array.
- randomize(double[][]) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
Randomize the 2d array based on an array, modify the array.
- randomize(Matrix) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
Randomize the matrix based on an array, modify the array.
- randomize(MLMethod) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
Randomize the synapses and biases in the basic network based on an array,
modify the array.
- randomize(double) - Method in class org.encog.mathutil.randomize.ConsistentRandomizer
-
Generate a random number based on the range specified in the constructor.
- randomize(BasicNetwork) - Method in class org.encog.mathutil.randomize.ConsistentRandomizer
-
Randomize the network.
- randomize(double) - Method in class org.encog.mathutil.randomize.ConstRandomizer
-
Generate a random number based on the range specified in the constructor.
- randomize(double) - Method in class org.encog.mathutil.randomize.Distort
-
Distort the random number by the factor that was specified in the
constructor.
- randomize(double) - Method in class org.encog.mathutil.randomize.FanInRandomizer
-
Starting with the specified number, randomize it to the degree specified
by this randomizer.
- randomize(double[]) - Method in class org.encog.mathutil.randomize.FanInRandomizer
-
Randomize the array based on an array, modify the array.
- randomize(double[][]) - Method in class org.encog.mathutil.randomize.FanInRandomizer
-
Randomize the 2d array based on an array, modify the array.
- randomize(Matrix) - Method in class org.encog.mathutil.randomize.FanInRandomizer
-
Randomize the matrix based on an array, modify the array.
- randomize(BasicNetwork, int) - Method in class org.encog.mathutil.randomize.FanInRandomizer
-
Randomize one level of a neural network.
- randomize(double) - Method in class org.encog.mathutil.randomize.GaussianRandomizer
-
Generate a random number.
- randomize(MLMethod) - Method in class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- randomize(double) - Method in class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- randomize(double[]) - Method in class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- randomize(double[][]) - Method in class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- randomize(Matrix) - Method in class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- randomize(double[], int, int) - Method in class org.encog.mathutil.randomize.NguyenWidrowRandomizer
-
- randomize(MLMethod) - Method in interface org.encog.mathutil.randomize.Randomizer
-
Randomize the synapses and bias values in the basic network based on an
array, modify the array.
- randomize(double) - Method in interface org.encog.mathutil.randomize.Randomizer
-
Starting with the specified number, randomize it to the degree specified
by this randomizer.
- randomize(double[]) - Method in interface org.encog.mathutil.randomize.Randomizer
-
Randomize the array based on an array, modify the array.
- randomize(double[][]) - Method in interface org.encog.mathutil.randomize.Randomizer
-
Randomize the 2d array based on an array, modify the array.
- randomize(Matrix) - Method in interface org.encog.mathutil.randomize.Randomizer
-
Randomize the matrix based on an array, modify the array.
- randomize(double[], int, int) - Method in interface org.encog.mathutil.randomize.Randomizer
-
Randomize an array.
- randomize(double, double) - Static method in class org.encog.mathutil.randomize.RangeRandomizer
-
Generate a random number in the specified range.
- randomize(Random, double, double) - Static method in class org.encog.mathutil.randomize.RangeRandomizer
-
- randomize(double) - Method in class org.encog.mathutil.randomize.RangeRandomizer
-
Generate a random number based on the range specified in the constructor.
- randomize() - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Randomize the weight matrix.
- randomize(int...) - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- randomize(Random, List<ValueType>, ProgramNode, double, double) - Method in class org.encog.ml.prg.extension.BasicTemplate
-
Randomize this actual tree node.
- randomize(Random, List<ValueType>, ProgramNode, double, double) - Method in interface org.encog.ml.prg.extension.ProgramExtensionTemplate
-
Randomize this actual tree node.
- randomize() - Method in class org.encog.neural.flat.FlatNetwork
-
Perform a simple randomization of the weights of the neural network
between -1 and 1.
- randomize(double, double) - Method in class org.encog.neural.flat.FlatNetwork
-
Perform a simple randomization of the weights of the neural network
between the specified hi and lo.
- randomize() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
Randomize the weights and bias values.
- randomize() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper
-
Call the owner's randomize method.
- RANDOMIZE_CONFIG_SOURCE_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "RANDOMIZE:CONFIG_sourceFile".
- RANDOMIZE_CONFIG_TARGET_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "RANDOMIZE:CONFIG_targetFile".
- randomizeNeuron(double, double, int, int) - Method in class org.encog.neural.prune.PruneSelective
-
- randomizeNeuron(int, int) - Method in class org.encog.neural.prune.PruneSelective
-
Assign random values to the network.
- Randomizer - Interface in org.encog.mathutil.randomize
-
Defines the interface for a class that is capable of randomizing the weights
and bias values of a neural network.
- randomizeRBFCentersAndWidths(double, double, RBFEnum) - Method in class org.encog.neural.rbf.RBFNetwork
-
Set the RBF components to random values.
- randomString() - Static method in class org.encog.util.http.FormUtility
-
Generate a random string, of a specified length.
- RandomTrainingFactory - Class in org.encog.util.benchmark
-
Class used to generate random training sets.
- RandomVariable - Class in org.encog.mathutil.probability.vars
-
- RandomVariable(String, String[]) - Constructor for class org.encog.mathutil.probability.vars.RandomVariable
-
- RandomVariable(String) - Constructor for class org.encog.mathutil.probability.vars.RandomVariable
-
- RangeNormalizer - Class in org.encog.ml.data.versatile.normalizers
-
A a range normalizer forces a value to fall in a specific range.
- RangeNormalizer(double, double) - Constructor for class org.encog.ml.data.versatile.normalizers.RangeNormalizer
-
Construct the range normalizer.
- RangeOrdinal - Class in org.encog.ml.data.versatile.normalizers
-
Normalize an ordinal into a specific range.
- RangeOrdinal(double, double) - Constructor for class org.encog.ml.data.versatile.normalizers.RangeOrdinal
-
- RangeRandomizer - Class in org.encog.mathutil.randomize
-
A randomizer that will create random weight and bias values that are between
a specified range.
- RangeRandomizer(double, double) - Constructor for class org.encog.mathutil.randomize.RangeRandomizer
-
Construct a range randomizer.
- RangeSegregator - Class in org.encog.util.normalize.segregate
-
Range segregators are used to segregate data and include or exclude if it is
within a certain range.
- RangeSegregator() - Constructor for class org.encog.util.normalize.segregate.RangeSegregator
-
Default constructor for reflection.
- RangeSegregator(InputField, boolean) - Constructor for class org.encog.util.normalize.segregate.RangeSegregator
-
Construct a range segregator.
- rank() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Effective numerical matrix rank
- RBF - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- RBFEnum - Enum in org.encog.mathutil.rbf
-
The implemented function types of the RBFs.
- RBFNetwork - Class in org.encog.neural.rbf
-
RBF neural network.
- RBFNetwork() - Constructor for class org.encog.neural.rbf.RBFNetwork
-
Construct RBF network.
- RBFNetwork(int, int, int, RBFEnum) - Constructor for class org.encog.neural.rbf.RBFNetwork
-
Construct RBF network.
- RBFNetwork(int, int, RadialBasisFunction[]) - Constructor for class org.encog.neural.rbf.RBFNetwork
-
Construct RBF network.
- RBFNetworkConfig - Class in org.encog.ml.model.config
-
Config class for EncogModel to use a RBF neural network.
- RBFNetworkConfig() - Constructor for class org.encog.ml.model.config.RBFNetworkConfig
-
- RBFNetworkFactory - Class in org.encog.ml.factory.method
-
A factory to create RBF networks.
- RBFNetworkFactory() - Constructor for class org.encog.ml.factory.method.RBFNetworkFactory
-
- RBFSVDFactory - Class in org.encog.ml.factory.train
-
This factory is used to create a SVD trainer for an RBF network.
- RBFSVDFactory() - Constructor for class org.encog.ml.factory.train.RBFSVDFactory
-
- read(InputStream) - Method in class org.encog.ca.universe.basic.PersistBasicUniverse
-
- read(InputStream) - Method in class org.encog.ml.bayesian.PersistBayes
-
Read the object from an input stream.
- read(double[], double[], double[]) - Method in class org.encog.ml.data.buffer.codec.ArrayDataCODEC
-
Read one record of data from an external source.
- read(double[], double[], double[]) - Method in class org.encog.ml.data.buffer.codec.CSVDataCODEC
-
Read one record of data from a CSV file.
- read(double[], double[], double[]) - Method in interface org.encog.ml.data.buffer.codec.DataSetCODEC
-
Read one record of data from an external source.
- read(double[], double[], double[]) - Method in class org.encog.ml.data.buffer.codec.ExcelCODEC
-
Read one record of data from an external source.
- read(double[], double[], double[]) - Method in class org.encog.ml.data.buffer.codec.NeuralDataSetCODEC
-
Read one record of data from an external source.
- read(double[], double[], double[]) - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
-
Read one record of data from an external source.
- read() - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Read a single double.
- read(double[]) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Read an array of doubles.
- read(int, double[]) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Read a double array at the specified record.
- read(int, int) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Read a row and column.
- read(InputStream) - Method in class org.encog.ml.hmm.PersistHMM
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.ml.prg.PersistPrgPopulation
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.ml.svm.PersistSVM
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.art.PersistART1
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.bam.PersistBAM
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.cpn.PersistCPN
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.neat.PersistNEATPopulation
-
- read(InputStream) - Method in class org.encog.neural.networks.PersistBasicNetwork
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.networks.training.propagation.PersistTrainingContinuation
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.pnn.PersistBasicPNN
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.rbf.PersistRBFNetwork
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.som.PersistSOM
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.thermal.PersistBoltzmann
-
Read the object from an input stream.
- read(InputStream) - Method in class org.encog.neural.thermal.PersistHopfield
-
Read the object from an input stream.
- read() - Method in class org.encog.parse.PeekableInputStream
-
Read a single byte from the stream.
- read() - Method in class org.encog.parse.tags.read.ReadTags
-
Read a single character from the HTML source, if this function returns
zero(0) then you should call getTag to see what tag was found.
- read(InputStream) - Method in interface org.encog.persist.EncogPersistor
-
Read the object from an input stream.
- read() - Method in class org.encog.util.text.Base64.InputStream
-
Reads enough of the input stream to convert
to/from Base64 and returns the next byte.
- read(byte[], int, int) - Method in class org.encog.util.text.Base64.InputStream
-
- readBIF(String) - Static method in class org.encog.ml.bayesian.bif.BIFUtil
-
Read a BIF file.
- readBIF(File) - Static method in class org.encog.ml.bayesian.bif.BIFUtil
-
- readBIF(InputStream) - Static method in class org.encog.ml.bayesian.bif.BIFUtil
-
Read a BIF file from a stream.
- readChar() - Method in class org.encog.util.SimpleParser
-
- ReadCSV - Class in org.encog.util.csv
-
Read and parse CSV format files.
- ReadCSV(InputStream, boolean, char) - Constructor for class org.encog.util.csv.ReadCSV
-
Construct a CSV reader from an input stream.
- ReadCSV(InputStream, boolean, CSVFormat) - Constructor for class org.encog.util.csv.ReadCSV
-
Construct a CSV reader from an input stream.
- ReadCSV(File, boolean, char) - Constructor for class org.encog.util.csv.ReadCSV
-
Construct a CSV reader from a filename.
- ReadCSV(String, boolean, char) - Constructor for class org.encog.util.csv.ReadCSV
-
- ReadCSV(String, boolean, CSVFormat) - Constructor for class org.encog.util.csv.ReadCSV
-
- ReadCSV(File, boolean, CSVFormat) - Constructor for class org.encog.util.csv.ReadCSV
-
Construct a CSV reader from a filename.
- readFileAsString(File) - Static method in class org.encog.util.file.FileUtil
-
- readHeaders(ReadCSV) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Read the headers from a CSV file.
- ReadHTML - Class in org.encog.parse.tags.read
-
This class is designed to parse HTML documents.
- ReadHTML(InputStream) - Constructor for class org.encog.parse.tags.read.ReadHTML
-
Construct a HTML reader.
- readIntToTag() - Method in class org.encog.parse.tags.read.ReadXML
-
Read an integer that is contained between the current position, and the
next tag.
- readLine() - Method in class org.encog.ml.data.versatile.sources.CSVDataSource
-
Read a line from the source.
- readLine() - Method in interface org.encog.ml.data.versatile.sources.VersatileDataSource
-
Read a line from the source.
- readNextSection() - Method in class org.encog.persist.EncogReadHelper
-
Read the next section.
- readPropertyBlock() - Method in class org.encog.parse.tags.read.ReadXML
-
Read all property data until an end tag, which corrisponds to the current
tag, is found.
- readQuotedString() - Method in class org.encog.util.SimpleParser
-
- readResourceAsString(String) - Static method in class org.encog.util.file.ResourceInputStream
-
- readStream(InputStream) - Static method in class org.encog.util.file.Directory
-
Read the entire contents of a stream into a string.
- readStreamAsString(InputStream) - Static method in class org.encog.util.file.FileUtil
-
- ReadTags - Class in org.encog.parse.tags.read
-
Base class used to read tags.
- ReadTags(InputStream) - Constructor for class org.encog.parse.tags.read.ReadTags
-
The constructor should be passed an InputStream that we will parse from.
- readTextFile(String) - Static method in class org.encog.util.file.Directory
-
Read the entire contents of a stream into a string.
- readTextToTag() - Method in class org.encog.parse.tags.read.ReadXML
-
Read all text between the current position and the next tag.
- readToChars(String) - Method in class org.encog.util.SimpleParser
-
- readToTag() - Method in class org.encog.parse.tags.read.ReadTags
-
Read until we reach the next tag.
- readToWhiteSpace() - Method in class org.encog.util.SimpleParser
-
- ReadXML - Class in org.encog.parse.tags.read
-
This class is designed to read XML.
- ReadXML(InputStream) - Constructor for class org.encog.parse.tags.read.ReadXML
-
Construct an XML reader.
- ready() - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer
-
- ready() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
- reanalyze(File, boolean, AnalystFileFormat) - Method in class org.encog.app.analyst.EncogAnalyst
-
Analyze the specified file.
- reanalyze() - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
Reanalyze column ranges.
- RECURRENT - Static variable in class org.encog.persist.PersistConst
-
Recurrent.
- ReflectionUtil - Class in org.encog.util.obj
-
This class includes some utilities to be used with reflection.
- register(FunctionFactory) - Method in class org.encog.app.analyst.csv.process.ProcessExtension
-
- registerError(Throwable) - Method in class org.encog.util.concurrency.EngineConcurrency
-
Allows threads to register errors, these errors will be thrown by the
main thread.
- registerPlugin(EncogPluginBase) - Method in class org.encog.Encog
-
Register a plugin.
- RegularizationStrategy - Class in org.encog.neural.networks.training.strategy
-
- RegularizationStrategy(double) - Constructor for class org.encog.neural.networks.training.strategy.RegularizationStrategy
-
- reInit(MLMethod) - Method in interface org.encog.ensemble.EnsembleMLMethodFactory
-
- reInit(MLMethod) - Method in class org.encog.ensemble.ml.mlp.factory.MultiLayerPerceptronFactory
-
- remaining() - Method in class org.encog.util.SimpleParser
-
- remove() - Method in class org.encog.ml.data.auto.AutoFloatDataSet.AutoFloatIterator
- remove(MLData) - Method in class org.encog.ml.data.basic.BasicMLDataCentroid
-
Remove an element from the centroid.
- remove(MLDataPair) - Method in class org.encog.ml.data.basic.BasicMLDataPairCentroid
-
Remove an element from the centroid.
- remove() - Method in class org.encog.ml.data.basic.BasicMLDataSet.BasicMLIterator
- remove() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet.BasicMLSeqIterator
- remove() - Method in class org.encog.ml.data.buffer.BufferedDataSetIterator
-
Not supported.
- remove() - Method in class org.encog.ml.data.folded.FoldedIterator
- remove() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet.MatrixMLDataSetIterator
- remove(MLDataPair, int) - Method in class org.encog.ml.hmm.train.kmeans.Clusters
-
- remove(MLData) - Method in class org.encog.ml.kmeans.BasicCluster
-
Remove the specified item.
- remove(MLData) - Method in interface org.encog.ml.MLCluster
-
Remove the specified item.
- remove(O) - Method in interface org.encog.util.kmeans.Centroid
-
Remove an element from the centroid.
- remove(int) - Method in class org.encog.util.kmeans.Cluster
-
Remove the specified index from the cluster.
- removeAdditional(BufferedMLDataSet) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Remove an additional dataset that was created.
- removeAgent(WorldAgent) - Method in class org.encog.ml.world.basic.BasicWorld
-
- removeAgent(WorldAgent) - Method in interface org.encog.ml.world.World
-
- removeAllRelations() - Method in class org.encog.ml.bayesian.BayesianEvent
-
Remove all relations.
- removeAllRelations() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Remove all relations between nodes.
- removeAnalystListener(AnalystListener) - Method in class org.encog.app.analyst.EncogAnalyst
-
Remove a listener.
- removeGoal(State) - Method in class org.encog.ml.world.basic.BasicWorld
-
- removeGoal(State) - Method in interface org.encog.ml.world.World
-
- removeNeuron(NEATGenome, long) - Method in class org.encog.neural.neat.training.opp.NEATMutation
-
Remove the specified neuron.
- removeRewardBelow(List<GridState>, double) - Static method in class org.encog.ml.world.basic.BasicWorld
-
- removeShutdownTask(EncogShutdownTask) - Method in class org.encog.Encog
-
Remove a shutdown task.
- removeSpecies(Species) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
Attempt to remove a removable species.
- renameColumn(int, String) - Method in class org.encog.app.quant.indicators.ProcessIndicators
-
Rename a column.
- render(EncogProgram) - Method in class org.encog.parse.expression.common.RenderCommonExpression
-
- render(EncogProgram) - Method in class org.encog.parse.expression.epl.RenderEPL
-
- render(EncogProgram) - Method in class org.encog.parse.expression.latex.RenderLatexExpression
-
- render(EncogProgram) - Method in class org.encog.parse.expression.rpn.RenderRPN
-
- RenderCommonExpression - Class in org.encog.parse.expression.common
-
Render a common expression.
- RenderCommonExpression() - Constructor for class org.encog.parse.expression.common.RenderCommonExpression
-
- RenderEPL - Class in org.encog.parse.expression.epl
-
- RenderEPL() - Constructor for class org.encog.parse.expression.epl.RenderEPL
-
- RenderLatexExpression - Class in org.encog.parse.expression.latex
-
- RenderLatexExpression() - Constructor for class org.encog.parse.expression.latex.RenderLatexExpression
-
- RenderRPN - Class in org.encog.parse.expression.rpn
-
- RenderRPN() - Constructor for class org.encog.parse.expression.rpn.RenderRPN
-
- replace(String, String, String) - Static method in class org.encog.util.EngineArray
-
- replaceNode(ProgramNode, ProgramNode) - Method in class org.encog.ml.prg.EncogProgram
-
Replace the specified node with another.
- report(int, int, String) - Method in interface org.encog.app.analyst.AnalystListener
-
Report progress on a task.
- report(int, int, String) - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Report progress on a task.
- report(int, int, String) - Method in class org.encog.app.analyst.util.AnalystReportBridge
-
Report on current status.
- report(int, int, String) - Method in class org.encog.ConsoleStatusReportable
-
Simply display any status reports.
- report(double[], double, Throwable) - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Called by the worker threads to report the progress at each step.
- report(int, int, String) - Method in class org.encog.NullStatusReportable
-
Simply ignore any status reports.
- report(int, int, String) - Method in interface org.encog.StatusReportable
-
Report on current status.
- REPORT_INTERVAL - Static variable in class org.encog.app.analyst.csv.basic.BasicFile
-
The default report interval.
- reportCommandBegin(int, int, String) - Method in interface org.encog.app.analyst.AnalystListener
-
Report that a command has begun.
- reportCommandBegin(int, int, String) - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Report that a command has begun.
- reportCommandEnd(boolean) - Method in interface org.encog.app.analyst.AnalystListener
-
Report that a command has ended.
- reportCommandEnd(boolean) - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Report that a command has ended.
- reportDone(boolean) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Report that we are done.
- reportDone(String) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Report that we are done.
- reportError(Throwable) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Called by a thread to report an error.
- reportStatus(JobUnitContext, String) - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
Report the status for this job.
- reportTraining(MLTrain) - Method in interface org.encog.app.analyst.AnalystListener
-
Report progress on training.
- reportTraining(MLTrain) - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Report progress on training.
- reportTraining(MLTrain) - Method in class org.encog.app.analyst.EncogAnalyst
-
Report training.
- reportTrainingBegin() - Method in interface org.encog.app.analyst.AnalystListener
-
Report that training has begun.
- reportTrainingBegin() - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Report that training has begun.
- reportTrainingBegin() - Method in class org.encog.app.analyst.EncogAnalyst
-
Report that training has begun.
- reportTrainingEnd() - Method in interface org.encog.app.analyst.AnalystListener
-
Report that training has ended.
- reportTrainingEnd() - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Report that training has ended.
- reportTrainingEnd() - Method in class org.encog.app.analyst.EncogAnalyst
-
Report that training has ended.
- requestCancelCommand() - Method in interface org.encog.app.analyst.AnalystListener
-
Request to cancel current command.
- requestCancelCommand() - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Request to cancel current command.
- requestNextTask() - Method in class org.encog.neural.prune.PruneIncremental
-
Request the next task.
- requestNextTask() - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
Request the next task to be processed.
- requestShutdown() - Method in interface org.encog.app.analyst.AnalystListener
-
Request stop the entire process.
- requestShutdown() - Method in class org.encog.app.analyst.ConsoleAnalystListener
-
Request stop the entire process.
- requestStop() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Request a stop.
- requestStop() - Method in class org.encog.app.quant.loader.yahoo.YahooDownload
-
Request to stop.
- requestStop() - Method in interface org.encog.app.quant.QuantTask
-
Request to stop.
- require(Map<String, BaseCachedColumn>, String) - Method in class org.encog.app.quant.indicators.Indicator
-
Require a specific type of underlying data.
- RequiredImprovementStrategy - Class in org.encog.ml.train.strategy
-
The reset strategy will reset the weights if the neural network fails to improve by the specified amount over a number of cycles.
- RequiredImprovementStrategy(double, int) - Constructor for class org.encog.ml.train.strategy.RequiredImprovementStrategy
-
Construct a reset strategy.
- RequiredImprovementStrategy(double, double, int) - Constructor for class org.encog.ml.train.strategy.RequiredImprovementStrategy
-
Construct a reset strategy.
- RequiredImprovementStrategy(int) - Constructor for class org.encog.ml.train.strategy.RequiredImprovementStrategy
-
Reset if there is not at least a 1% improvement for 5 cycles.
- requireEvent(String) - Method in class org.encog.mathutil.probability.vars.VariableList
-
- requireEvent(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Require the specified event, thrown an error if it does not exist.
- requireFlat() - Method in class org.encog.neural.networks.structure.NeuralStructure
-
Throw an error if there is no flat network.
- requireSingleThreaded() - Method in interface org.encog.ml.CalculateScore
-
- requireSingleThreaded() - Method in class org.encog.ml.ea.score.EmptyScoreFunction
- requireSingleThreaded() - Method in class org.encog.ml.fitness.MultiObjectiveFitness
- requireSingleThreaded() - Method in class org.encog.ml.prg.train.ZeroEvalScoreFunction
- requireSingleThreaded() - Method in class org.encog.neural.networks.training.TrainingSetScore
-
- RequireTwoPass - Interface in org.encog.util.normalize.output
-
Interface flag that indicates that a field type requires two passes.
- ResamplingDataSetFactory - Class in org.encog.ensemble.data.factories
-
- ResamplingDataSetFactory(int) - Constructor for class org.encog.ensemble.data.factories.ResamplingDataSetFactory
-
- reset() - Method in class org.encog.ca.runner.BasicCARunner
-
- reset() - Method in interface org.encog.ca.runner.CARunner
-
- reset() - Method in class org.encog.mathutil.error.ErrorCalculation
-
Reset the error accumulation to zero.
- reset() - Method in class org.encog.ml.bayesian.BayesianEvent
-
Reset the logic table.
- reset() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Reset the weights.
- reset(int) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Reset the weights with a seed.
- reset() - Method in class org.encog.ml.bayesian.query.BasicQuery
-
Reset all event types back to hidden.
- reset() - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
Reset all event types back to hidden.
- reset() - Method in class org.encog.ml.bayesian.table.BayesianTable
-
Reset the truth table to zero.
- reset() - Method in interface org.encog.ml.MLResettable
-
Reset the weights.
- reset(int) - Method in interface org.encog.ml.MLResettable
-
Reset the weights with a seed.
- reset() - Method in class org.encog.neural.art.ART1
-
Reset the weight matrix back to starting values.
- reset(int) - Method in class org.encog.neural.art.ART1
-
Reset with a specic seed.
- reset() - Method in class org.encog.neural.cpn.CPN
-
Reset the weights.
- reset(int) - Method in class org.encog.neural.cpn.CPN
-
Reset the weights with a seed.
- reset() - Method in class org.encog.neural.freeform.FreeformNetwork
-
Reset the weights.
- reset(int) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Reset the weights with a seed.
- reset() - Method in class org.encog.neural.neat.NEATPopulation
-
Create an initial random population.
- reset() - Method in class org.encog.neural.networks.BasicNetwork
-
Reset the weight matrix and the bias values.
- reset(int) - Method in class org.encog.neural.networks.BasicNetwork
-
Reset the weight matrix and the bias values.
- reset() - Method in class org.encog.neural.rbf.RBFNetwork
-
Reset the weights.
- reset(int) - Method in class org.encog.neural.rbf.RBFNetwork
-
Reset the weights with a seed.
- reset() - Method in class org.encog.neural.som.SOM
-
Reset the weights.
- reset(int) - Method in class org.encog.neural.som.SOM
-
Reset the weights with a seed.
- reset() - Method in class org.encog.neural.som.training.basic.BestMatchingUnit
-
Reset the "worst distance" back to a minimum value.
- reset() - Method in class org.encog.neural.thermal.ThermalNetwork
-
Reset the weights.
- reset(int) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Reset the weights with a seed.
- reset() - Method in class org.encog.util.SimpleParser
-
- reset() - Method in class org.encog.util.Stopwatch
-
Reset the stop watch.
- resetConfusion() - Method in class org.encog.neural.pnn.AbstractPNN
-
Reset the confusion.
- resetEnumeration(boolean, boolean) - Method in class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
-
Reset the enumeration events.
- resetStatus() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Reset the reporting stats.
- ResetStrategy - Class in org.encog.ml.train.strategy
-
The reset strategy will reset the weights if the neural network fails to fall
below a specified error by a specified number of cycles.
- ResetStrategy(double, int) - Constructor for class org.encog.ml.train.strategy.ResetStrategy
-
Construct a reset strategy.
- ResilientPropagation - Class in org.encog.neural.networks.training.propagation.resilient
-
One problem with the backpropagation algorithm is that the magnitude of the
partial derivative is usually too large or too small.
- ResilientPropagation(ContainsFlat, MLDataSet) - Constructor for class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Construct an RPROP trainer, allows an OpenCL device to be specified.
- ResilientPropagation(ContainsFlat, MLDataSet, double, double) - Constructor for class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Construct a resilient training object, allow the training parameters to
be specified.
- ResilientPropagationFactory - Class in org.encog.ensemble.training
-
- ResilientPropagationFactory() - Constructor for class org.encog.ensemble.training.ResilientPropagationFactory
-
- resolveEncogClass(String) - Static method in class org.encog.util.obj.ReflectionUtil
-
Resolve an encog class using its simple name.
- resolveEnum(Field, String) - Static method in class org.encog.util.obj.ReflectionUtil
-
Resolve an enumeration.
- resolveFilename(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
Resolve the specified filename.
- resolveValue(BayesianEvent) - Method in class org.encog.ml.bayesian.parse.ParsedEvent
-
Resolve the event to an actual value.
- ResourceInputStream - Class in org.encog.util.file
-
- ResourceInputStream() - Constructor for class org.encog.util.file.ResourceInputStream
-
- ResourceLoader - Class in org.encog.util
-
Used to load resources from the JAR file.
- resume(TrainingContinuation) - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.ml.fitting.gaussian.TrainGaussian
-
- resume(TrainingContinuation) - Method in class org.encog.ml.fitting.linear.TrainLinearRegression
-
- resume(TrainingContinuation) - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- resume(TrainingContinuation) - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- resume(TrainingContinuation) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.ml.svm.training.SVMTrain
-
Resume training.
- resume(TrainingContinuation) - Method in interface org.encog.ml.train.MLTrain
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.cpn.training.TrainInstar
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.cpn.training.TrainOutstar
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.freeform.training.FreeformBackPropagation
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.cross.CrossValidationKFold
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.nm.NelderMeadTraining
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
This training type does not support training continue.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
This training type does not support training continue.
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
- resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.simple.TrainAdaline
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.rbf.training.SVDTraining
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Resume training.
- resume(TrainingContinuation) - Method in class org.encog.neural.som.training.clustercopy.SOMClusterCopyTraining
-
Resume training.
- resumeEncoding() - Method in class org.encog.util.text.Base64.OutputStream
-
Resumes encoding of the stream.
- reverseOfAction(Action) - Static method in class org.encog.ml.world.grid.GridWorld
-
- rewind() - Method in class org.encog.ml.data.versatile.sources.CSVDataSource
-
Rewind the source back to the beginning.
- rewind() - Method in interface org.encog.ml.data.versatile.sources.VersatileDataSource
-
Rewind the source back to the beginning.
- rewrite(Genome) - Method in class org.encog.ml.ea.rules.BasicRuleHolder
-
Rewrite the specified genome.
- rewrite(Genome) - Method in interface org.encog.ml.ea.rules.RewriteRule
-
Rewrite the specified genome.
- rewrite(Genome) - Method in interface org.encog.ml.ea.rules.RuleHolder
-
Rewrite the specified genome.
- rewrite(Genome) - Method in class org.encog.ml.prg.train.rewrite.RewriteAlgebraic
-
Rewrite the specified genome.
- rewrite(Genome) - Method in class org.encog.ml.prg.train.rewrite.RewriteBoolean
-
Rewrite the specified genome.
- rewrite(Genome) - Method in class org.encog.ml.prg.train.rewrite.RewriteConstants
-
Rewrite the specified genome.
- RewriteAlgebraic - Class in org.encog.ml.prg.train.rewrite
-
This class is used to rewrite algebraic expressions into more simple forms.
- RewriteAlgebraic() - Constructor for class org.encog.ml.prg.train.rewrite.RewriteAlgebraic
-
- RewriteBoolean - Class in org.encog.ml.prg.train.rewrite
-
Basic rewrite rules for boolean expressions.
- RewriteBoolean() - Constructor for class org.encog.ml.prg.train.rewrite.RewriteBoolean
-
- RewriteConstants - Class in org.encog.ml.prg.train.rewrite
-
Rewrite any parts of the tree that are constant with a simple constant value.
- RewriteConstants() - Constructor for class org.encog.ml.prg.train.rewrite.RewriteConstants
-
- RewriteRule - Interface in org.encog.ml.ea.rules
-
Defines a rewrite rule.
- RGBDownsample - Class in org.encog.util.downsample
-
Downsample an image keeping the RGB colors.
- RGBDownsample() - Constructor for class org.encog.util.downsample.RGBDownsample
-
- rho - Variable in class org.encog.mathutil.libsvm.svm_model
-
- rightOfAction(Action) - Static method in class org.encog.ml.world.grid.GridWorld
-
- roll(List<BayesianEvent>, int[]) - Static method in class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
-
Roll the enumeration events forward by one.
- rollArgs(double[]) - Method in class org.encog.ml.bayesian.BayesianEvent
-
Roll the specified arguments through all of the possible values, return
false if we are at the final iteration.
- rollArgs(BayesianEvent, int[]) - Static method in class org.encog.ml.bayesian.bif.BIFUtil
-
Iterate through the event arguments in the BIF way, which is different
than Encog's method.
- rollIndex() - Method in class org.encog.util.normalize.segregate.index.IndexSegregator
-
Used to increase the current index as data is processed.
- rollIteration() - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Increase the iteration by one.
- RowComparator - Class in org.encog.app.analyst.csv.sort
-
Used to compare two LoadedRow objects.
- RowComparator(SortCSV) - Constructor for class org.encog.app.analyst.csv.sort.RowComparator
-
Construct the object.
- rowInit() - Method in class org.encog.util.normalize.output.mapped.OutputFieldEncode
-
Not needed for this sort of output field.
- rowInit() - Method in class org.encog.util.normalize.output.multiplicative.MultiplicativeGroup
-
Called to init this group for a new field.
- rowInit() - Method in class org.encog.util.normalize.output.multiplicative.OutputFieldMultiplicative
-
Not needed for this sort of output field.
- rowInit() - Method in class org.encog.util.normalize.output.nominal.OutputEquilateral
-
Determine which item's index is the value.
- rowInit() - Method in class org.encog.util.normalize.output.nominal.OutputOneOf
-
Not needed for this sort of output field.
- rowInit() - Method in interface org.encog.util.normalize.output.OutputField
-
Init this field for a new row.
- rowInit() - Method in class org.encog.util.normalize.output.OutputFieldDirect
-
Not needed for this sort of output field.
- rowInit() - Method in interface org.encog.util.normalize.output.OutputFieldGroup
-
Init the group for a new row.
- rowInit() - Method in class org.encog.util.normalize.output.OutputFieldRangeMapped
-
Not needed for this sort of output field.
- rowInit() - Method in class org.encog.util.normalize.output.zaxis.OutputFieldZAxis
-
Not needed for this sort of output field.
- rowInit() - Method in class org.encog.util.normalize.output.zaxis.OutputFieldZAxisSynthetic
-
Not needed for this sort of output field.
- rowInit() - Method in class org.encog.util.normalize.output.zaxis.ZAxisGroup
-
Initialize this group for a new row.
- ROWS - Static variable in class org.encog.persist.PersistConst
-
- RPROPConst - Class in org.encog.neural.networks.training.propagation.resilient
-
Constants used for Resilient Propagation (RPROP) training.
- RPROPFactory - Class in org.encog.ml.factory.train
-
A factory that creates RPROP trainers.
- RPROPFactory() - Constructor for class org.encog.ml.factory.train.RPROPFactory
-
- RPROPJob - Class in org.encog.neural.networks.training.concurrent.jobs
-
A training definition for RPROP training.
- RPROPJob(BasicNetwork, MLDataSet, boolean) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
-
Construct an RPROP job.
- RPROPType - Enum in org.encog.neural.networks.training.propagation.resilient
-
Allows the type of RPROP to be defined.
- RSS - Class in org.encog.bot.rss
-
This is the class that actually parses the RSS and builds a collection of
RSSItems.
- RSS() - Constructor for class org.encog.bot.rss.RSS
-
- RSSItem - Class in org.encog.bot.rss
-
This is the class that holds individual RSS items, or stories, for the RSS
class.
- RSSItem() - Constructor for class org.encog.bot.rss.RSSItem
-
- RuleHolder - Interface in org.encog.ml.ea.rules
-
Holds a set of rules for an EA.
- run() - Method in class org.encog.ca.runner.BasicCARunner
-
- run() - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
The task to perform.
- run() - Method in class org.encog.ml.ea.score.parallel.ParallelScoreTask
-
Perform the task.
- run() - Method in class org.encog.ml.prg.generator.GenerateWorker
- run() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Perform the training.
- run() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
- run() - Method in class org.encog.neural.networks.training.concurrent.performers.PerformerTask
-
Run the task.
- run() - Method in class org.encog.neural.networks.training.propagation.GradientWorker
-
Perform the gradient calculation for the specified index range.
- run(int) - Method in class org.encog.neural.networks.training.propagation.GradientWorker
-
- run() - Method in class org.encog.neural.networks.training.pso.NeuralPSOWorker
-
Update the particle velocity, position and personal best.
- run() - Method in class org.encog.neural.thermal.BoltzmannMachine
-
Run the network for all neurons present.
- run(int) - Method in class org.encog.neural.thermal.BoltzmannMachine
-
Run the network for the specified neuron.
- run() - Method in class org.encog.neural.thermal.HopfieldNetwork
-
Perform one Hopfield iteration.
- run() - Method in interface org.encog.util.concurrency.EngineTask
-
The task to perform.
- run() - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
- run() - Method in class org.encog.util.concurrency.job.JobUnitWorker
-
Run this job unit.
- run() - Method in class org.encog.util.concurrency.PoolItem
-
Run the task.
- RUN_CYCLES - Static variable in class org.encog.neural.thermal.BoltzmannMachine
-
The property for run cycles.
- runToConverge(int) - Method in class org.encog.ca.runner.BasicCARunner
-
- runToConverge(int, double) - Method in class org.encog.ca.runner.BasicCARunner
-
- runToConverge(int, double) - Method in interface org.encog.ca.runner.CARunner
-
- runToGoal(WorldAgent) - Method in class org.encog.ml.world.basic.BasicWorld
-
- runToGoal(WorldAgent) - Method in interface org.encog.ml.world.World
-
- runUntilStable(int) - Method in class org.encog.neural.thermal.HopfieldNetwork
-
Run the network until it becomes stable and does not change from more
runs.
- safeHashCode(T) - Static method in class org.encog.util.obj.ReflectionUtil
-
Generate a hash code for an object.
- SamplingQuery - Class in org.encog.ml.bayesian.query.sample
-
A sampling query allows probabilistic queries on a Bayesian network.
- SamplingQuery(BayesianNetwork) - Constructor for class org.encog.ml.bayesian.query.sample.SamplingQuery
-
Construct a sampling query.
- satisfiesDesiredOutcome() - Method in class org.encog.ml.bayesian.query.BasicQuery
-
- save(File) - Method in class org.encog.app.analyst.EncogAnalyst
-
Save the script to a file.
- save(OutputStream) - Method in class org.encog.app.analyst.EncogAnalyst
-
Save the script to a stream.
- save(String) - Method in class org.encog.app.analyst.EncogAnalyst
-
Save the script to a filename.
- save(OutputStream) - Method in class org.encog.app.analyst.script.AnalystScript
-
Save to the specified output stream.
- save(OutputStream) - Method in class org.encog.app.analyst.script.ScriptSave
-
Save the script to a stream.
- save() - Method in class org.encog.app.generate.EncogCodeGeneration
-
Save the contents to a string.
- save(File) - Method in class org.encog.app.generate.EncogCodeGeneration
-
Save the contents to the specified file.
- save(CARunner, File) - Static method in class org.encog.ca.program.generic.GenericIO
-
- save(OutputStream, Object) - Method in class org.encog.ca.universe.basic.PersistBasicUniverse
-
- save(OutputStream, Object) - Method in class org.encog.ml.bayesian.PersistBayes
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.ml.hmm.PersistHMM
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.ml.prg.PersistPrgPopulation
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.ml.svm.PersistSVM
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.art.PersistART1
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.bam.PersistBAM
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.cpn.PersistCPN
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.neat.PersistNEATPopulation
-
- save(OutputStream, Object) - Method in class org.encog.neural.networks.PersistBasicNetwork
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.networks.training.propagation.PersistTrainingContinuation
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.pnn.PersistBasicPNN
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.rbf.PersistRBFNetwork
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.som.PersistSOM
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.thermal.PersistBoltzmann
-
Save the object.
- save(OutputStream, Object) - Method in class org.encog.neural.thermal.PersistHopfield
-
Save the object.
- save(OutputStream, Object) - Method in interface org.encog.persist.EncogPersistor
-
Save the object.
- save(File, Serializable) - Static method in class org.encog.util.obj.SerializeObject
-
Save the specified object.
- saveCookies(URLConnection) - Method in class org.encog.util.http.CookieUtility
-
Once you have loaded cookies with loadCookies, you can call saveCookies
to copy these cookies to a new HTTP request.
- saveCSV(File, CSVFormat, MLDataSet) - Static method in class org.encog.util.simple.EncogUtility
-
- saveEGB(File, MLDataSet) - Static method in class org.encog.util.simple.EncogUtility
-
Save a training set to an EGB file.
- saveObject(File, Object) - Static method in class org.encog.persist.EncogDirectoryPersistence
-
Save the specified object.
- saveObject(OutputStream, Object) - Static method in class org.encog.persist.EncogDirectoryPersistence
-
Save the specified object.
- saveToDirectory(String, Object) - Method in class org.encog.persist.EncogDirectoryPersistence
-
Save a file to the directory that this object refers to.
- SCALE_LAMBDA - Static variable in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
The amount to scale the lambda by.
- ScaledConjugateGradient - Class in org.encog.neural.networks.training.propagation.scg
-
This is a training class that makes use of scaled conjugate gradient methods.
- ScaledConjugateGradient(ContainsFlat, MLDataSet) - Constructor for class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient
-
Construct a training class.
- ScaledConjugateGradientFactory - Class in org.encog.ensemble.training
-
- ScaledConjugateGradientFactory() - Constructor for class org.encog.ensemble.training.ScaledConjugateGradientFactory
-
- SCGFactory - Class in org.encog.ml.factory.train
-
A factory used to create SCG trainers.
- SCGFactory() - Constructor for class org.encog.ml.factory.train.SCGFactory
-
- ScheduleGraph - Class in org.encog.ml.schedule
-
- ScheduleGraph() - Constructor for class org.encog.ml.schedule.ScheduleGraph
-
- ScriptLoad - Class in org.encog.app.analyst.script
-
Used to load an Encog Analyst script.
- ScriptLoad(AnalystScript) - Constructor for class org.encog.app.analyst.script.ScriptLoad
-
Construct a script loader.
- ScriptOpcode - Class in org.encog.app.analyst.script.ml
-
An opcode, stored in the script.
- ScriptOpcode(ProgramExtensionTemplate) - Constructor for class org.encog.app.analyst.script.ml.ScriptOpcode
-
- ScriptOpcode(String, int) - Constructor for class org.encog.app.analyst.script.ml.ScriptOpcode
-
Construct the opcode.
- ScriptProperties - Class in org.encog.app.analyst.script.prop
-
Holds all of the properties for a script.
- ScriptProperties() - Constructor for class org.encog.app.analyst.script.prop.ScriptProperties
-
- ScriptSave - Class in org.encog.app.analyst.script
-
Used to save an Encog Analyst script.
- ScriptSave(AnalystScript) - Constructor for class org.encog.app.analyst.script.ScriptSave
-
Construct the script.
- sdev(int[]) - Static method in class org.encog.util.EngineArray
-
- search(String) - Method in class org.encog.util.YahooSearch
-
Called to extract a list from the specified URL.
- SearchGoal - Interface in org.encog.ml.graph.search
-
- SearchK2 - Class in org.encog.ml.bayesian.training.search.k2
-
Search for optimal Bayes structure with K2.
- SearchK2() - Constructor for class org.encog.ml.bayesian.training.search.k2.SearchK2
-
- SearchNone - Class in org.encog.ml.bayesian.training.search
-
Simple class to perform no search for optimal network structure.
- SearchNone() - Constructor for class org.encog.ml.bayesian.training.search.SearchNone
-
- SECONDS_INA_DAY - Static variable in class org.encog.util.Format
-
Seconds in a day.
- SECONDS_INA_HOUR - Static variable in class org.encog.util.Format
-
Seconds in an hour.
- SECONDS_INA_MINUTE - Static variable in class org.encog.util.Format
-
Seconds in a minute.
- SECONDS_MINUTE - Static variable in class org.encog.util.time.TimeSpan
-
Seconds in a minute.
- SecureGenerateRandom - Class in org.encog.mathutil.randomize.generate
-
A wrapper over Java's crypto secure random number generator.
- SecureGenerateRandom(long) - Constructor for class org.encog.mathutil.randomize.generate.SecureGenerateRandom
-
Construct the random number generator.
- SecureGenerateRandom() - Constructor for class org.encog.mathutil.randomize.generate.SecureGenerateRandom
-
Construct with a time-based seed.
- SEGREGATE_CONFIG_SOURCE_FILE - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "SEGREGATE:CONFIG_sourceFile".
- SegregateCSV - Class in org.encog.app.analyst.csv.segregate
-
This class is used to segregate a CSV file into several sub-files.
- SegregateCSV() - Constructor for class org.encog.app.analyst.csv.segregate.SegregateCSV
-
- SegregateTargetPercent - Class in org.encog.app.analyst.csv.segregate
-
Specifies a segregation target, and what percent that target should need.
- SegregateTargetPercent(File, int) - Constructor for class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
-
Construct the object.
- SegregationRange - Class in org.encog.util.normalize.segregate
-
Specifies a range that might be included or excluded.
- SegregationRange() - Constructor for class org.encog.util.normalize.segregate.SegregationRange
-
Default constructor for reflection.
- SegregationRange(double, double, boolean) - Constructor for class org.encog.util.normalize.segregate.SegregationRange
-
Construct a segregation range.
- Segregator - Interface in org.encog.util.normalize.segregate
-
Segregators are used to exclude certain rows.
- SelectFixed - Class in org.encog.neural.neat.training.opp.links
-
Select a fixed number of link genes.
- SelectFixed(int) - Constructor for class org.encog.neural.neat.training.opp.links.SelectFixed
-
Construct a fixed count link selector.
- SelectionOperator - Interface in org.encog.ml.ea.opp.selection
-
Provides the interface to a selection operator.
- selectLinks(Random, NEATGenome) - Method in class org.encog.neural.neat.training.opp.links.SelectFixed
-
Select links from the specified genome.
- SelectLinks - Interface in org.encog.neural.neat.training.opp.links
-
This interface defines ways that NEAT links can be chosen for mutation.
- selectLinks(Random, NEATGenome) - Method in interface org.encog.neural.neat.training.opp.links.SelectLinks
-
Select links from the specified genome.
- selectLinks(Random, NEATGenome) - Method in class org.encog.neural.neat.training.opp.links.SelectProportion
-
Select links from the specified genome.
- selectMethod(VersatileMLDataSet, String, String, String, String) - Method in class org.encog.ml.model.EncogModel
-
Select the method to use.
- selectMethod(VersatileMLDataSet, String) - Method in class org.encog.ml.model.EncogModel
-
Select the method to create.
- SelectProportion - Class in org.encog.neural.neat.training.opp.links
-
Select a random proportion of links to mutate.
- SelectProportion(double) - Constructor for class org.encog.neural.neat.training.opp.links.SelectProportion
-
Select based on proportion.
- selectRandomVariable(Random, List<ValueType>) - Method in class org.encog.ml.prg.EncogProgram
-
Select a random variable from the defined variables.
- selectTraining(VersatileMLDataSet, String, String) - Method in class org.encog.ml.model.EncogModel
-
Select the training to use.
- selectTrainingType(VersatileMLDataSet) - Method in class org.encog.ml.model.EncogModel
-
Select the training type.
- SerializeObject - Class in org.encog.util.obj
-
Load or save an object using Java serialization.
- set(int, double) - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- set(int, double[]) - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- set(int, double) - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- set(int, double[]) - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- set(int, double[]) - Method in interface org.encog.ca.universe.ContinuousCell
-
- set(int, double) - Method in interface org.encog.ca.universe.UniverseCell
-
- set(int, double[]) - Method in interface org.encog.ca.universe.UniverseCell
-
- set(double) - Method in class org.encog.mathutil.matrices.Matrix
-
Set every value in the matrix to the specified value.
- set(int, int, double) - Method in class org.encog.mathutil.matrices.Matrix
-
Set an individual cell in the matrix to the specified value.
- set(Matrix) - Method in class org.encog.mathutil.matrices.Matrix
-
Set this matrix's values to that of another matrix.
- set(String, Object) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
-
Set a value to a string.
- setA1(double) - Method in class org.encog.neural.art.ART1
-
Set the A1 parameter.
- setA1(double) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the A1 parameter.
- setAction(NormalizationAction) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Set the theAction for the field.
- setAction(Address) - Method in class org.encog.bot.browse.range.Form
-
Set the action for the form.
- setAction(NormalizationAction) - Method in class org.encog.util.arrayutil.NormalizedField
-
Set the action for the field.
- setAction(TemporalType) - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- setActivation(ActivationFunction) - Method in class org.encog.neural.flat.FlatLayer
-
- setActivation(int, double) - Method in class org.encog.neural.freeform.basic.BasicFreeformLayer
-
Set the activation for the specified index.
- setActivation(double) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Set the activation, or final output for this neuron.
- setActivation(int, double) - Method in interface org.encog.neural.freeform.FreeformLayer
-
Set the activation for the specified index.
- setActivation(double) - Method in interface org.encog.neural.freeform.FreeformNeuron
-
Set the activation, or final output for this neuron.
- setActivation(ActivationFunction) - Method in interface org.encog.neural.networks.layers.Layer
-
Set the activation function.
- setActivationCycles(int) - Method in class org.encog.neural.hyperneat.substrate.Substrate
-
- setActivationCycles(int) - Method in class org.encog.neural.neat.NEATNetwork
-
Set the number of activation cycles to use.
- setActivationCycles(int) - Method in class org.encog.neural.neat.NEATPopulation
-
Set the number of activation cycles to use.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.freeform.basic.BasicActivationSummation
-
Set the activation function.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.neat.training.NEATNeuronGene
-
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ADALINEPattern
-
Not used, ADALINE does not use custom activation functions.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ART1Pattern
-
This method will throw an error, you can't set the activation function
for an ART1.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.BAMPattern
-
Not used, the BAM uses a bipoloar activation function.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Not used, will throw an exception.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.CPNPattern
-
This method will throw an error.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ElmanPattern
-
Set the activation function to use on each of the layers.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.FeedForwardPattern
-
Set the activation function to use on each of the layers.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.HopfieldPattern
-
Set the activation function to use.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.JordanPattern
-
Set the activation function to use on each of the layers.
- setActivationFunction(ActivationFunction) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern
-
Set the activation function to be used for all created layers that allow
an activation function to be specified.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.PNNPattern
-
Set the activation function.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.RadialBasisPattern
-
Set the activation function, this is an error.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.SOMPattern
-
Set the activation function.
- setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.SVMPattern
-
Not used, the BAM uses a bipoloar activation function.
- setActivationFunctions(ActivationFunction[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the activation functions.
- setActivationOutput(ActivationFunction) - Method in class org.encog.neural.pattern.FeedForwardPattern
-
- setActualHigh(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Set the actual high for the field.
- setActualHigh(double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Set the actual high for the field.
- setActualLow(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Set the actual low for the field.
- setActualLow(double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Set the actual low for the field.
- setAdjustedScore(double) - Method in class org.encog.ml.ea.genome.BasicGenome
-
Set the adjusted score.
- setAdjustedScore(double) - Method in interface org.encog.ml.ea.genome.Genome
-
Set the adjusted score.
- setAge(int) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Set the age of this species.
- setAge(int) - Method in interface org.encog.ml.ea.species.Species
-
Set the age of this species.
- setAgentPolicy(AgentPolicy) - Method in class org.encog.ml.world.basic.BasicAgent
-
- setAgentPolicy(AgentPolicy) - Method in interface org.encog.ml.world.WorldAgent
-
- setAggregator(EnsembleAggregator) - Method in class org.encog.ensemble.Ensemble
-
Sets the ensemble aggregation method
- setAllPolicyValues(double) - Method in class org.encog.ml.world.basic.BasicState
-
- setAllPolicyValues(double) - Method in interface org.encog.ml.world.State
-
- setAllRewards(double) - Method in class org.encog.ml.world.basic.BasicWorld
-
- setAllRewards(double) - Method in interface org.encog.ml.world.World
-
- setAnalyzed(boolean) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set to true, if the file has been analyzed.
- setAnnealCycles(int) - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Set the number of annealing cycles per run.
- setAnnealCycles(int) - Method in class org.encog.neural.thermal.BoltzmannMachine
-
- setAscending(boolean) - Method in class org.encog.app.analyst.csv.sort.SortedField
-
- setAttribute(String, String) - Method in class org.encog.parse.tags.Tag
-
Set a HTML attribute.
- setAutoDecay(int, double, double, double, double) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Setup autodecay.
- setB1(double) - Method in class org.encog.neural.art.ART1
-
Set the B1 parameter.
- setB1(double) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the B1 parameter.
- setBasePath(String) - Method in class org.encog.app.analyst.script.AnalystScript
-
Set the base path.
- setBatchSize(int) - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Set the batch size.
- setBatchSize(int) - Method in interface org.encog.neural.networks.training.BatchSize
-
Set the batch size.
- setBatchSize(int) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
Do not allow batch sizes other than 0, not supported.
- setBatchSize(int) - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Set the batch size.
- setBatchSize(int) - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
Do not allow batch sizes other than 0, not supported.
- setBegin(int) - Method in class org.encog.bot.browse.range.DocumentRange
-
Set the beginning index.
- setBeginningIndex(int) - Method in class org.encog.app.quant.indicators.Indicator
-
- setBeginTraining(int) - Method in class org.encog.neural.flat.FlatNetwork
-
- setBestComparator(GenomeComparator) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the comparator.
- setBestComparator(GenomeComparator) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Set the comparator that is used to choose the "true best" genome.
- setBestConst(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setBestGamma(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setBestGenome(Genome) - Method in class org.encog.ml.ea.population.BasicPopulation
-
Set the best genome.
- setBestGenome(Genome) - Method in interface org.encog.ml.ea.population.Population
-
Set the best genome.
- setBestScore(double) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Set the best score for this species.
- setBestScore(double) - Method in interface org.encog.ml.ea.species.Species
-
Set the best score for this species.
- setBias(boolean) - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- setBias(boolean) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Determine if this neuron is a bias neuron.
- setBias(boolean) - Method in interface org.encog.neural.freeform.FreeformNeuron
-
Determine if this neuron is a bias neuron.
- setBiasActivation(double) - Method in class org.encog.neural.flat.FlatLayer
-
Set the bias activation.
- setBiasActivation(double[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the bias activation.
- setBiasActivation(double) - Method in class org.encog.neural.networks.BasicNetwork
-
Sets the bias activation for every layer that supports bias.
- setBiasActivation(double) - Method in interface org.encog.neural.networks.layers.Layer
-
Most layer types will default this value to one.
- setBirthGeneration(int) - Method in class org.encog.ml.ea.genome.BasicGenome
-
- setBirthGeneration(int) - Method in interface org.encog.ml.ea.genome.Genome
-
Set the birth genertion (or iteration).
- setBlocked(int, int) - Method in class org.encog.ml.world.grid.GridWorld
-
- setBreakSpaces(boolean) - Method in class org.encog.util.text.BagOfWords
-
- setBufferSize(int) - Method in class org.encog.app.analyst.csv.shuffle.ShuffleCSV
-
Set the buffer size.
- setC(double) - Method in class org.encog.ml.svm.training.SVMTrain
-
Set the constant C.
- setC1(double) - Method in class org.encog.neural.art.ART1
-
Set the C1 parameter.
- setC1(double) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Sets the cognition coefficient (c1).
- setC1(double) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the C1 parameter.
- setC2(double) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Set the social coefficient (c2).
- setCalculated(boolean) - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- setCalculatedIdealSize(int) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- setCalculatedInputSize(int) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- setCatchAll(double) - Method in class org.encog.util.normalize.output.mapped.OutputFieldEncode
-
Set the catch all value.
- setCenter(double) - Method in class org.encog.engine.network.activation.ActivationStep
-
Set the center of this function.
- setCenters(double[]) - Method in class org.encog.mathutil.rbf.BasicRBF
-
Set the centers.
- setCenters(double[]) - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
Set the centers.
- setCentroid(BasicMLDataPairCentroid) - Method in class org.encog.ml.kmeans.BasicCluster
-
Set the centroid.
- setChampMutation(EvolutionaryOperator) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- setClass(boolean) - Method in class org.encog.app.analyst.script.DataField
-
- setClassAttribute(String) - Method in class org.encog.bot.browse.range.DocumentRange
-
- setCode(String) - Method in class org.encog.app.analyst.script.AnalystClassItem
-
- setCode(String) - Method in class org.encog.bot.dataunit.CodeDataUnit
-
Set the code to the specified string.
- setCODEC(GeneticCODEC) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the CODEC to use.
- setCODEC(GeneticCODEC) - Method in class org.encog.neural.neat.NEATPopulation
-
- setCodeEmbedData(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setCodeTargetLanguage(TargetLanguage) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setColumnCount(int) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the column count.
- setCompareValue(int) - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- setCompatibilityThreshold(double) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- setComplete(boolean) - Method in class org.encog.app.analyst.script.DataField
-
- setComplexityFullPenalty(double) - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- setComplexityPenalty(double) - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- setComplexityPenaltyThreshold(int) - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- setComplexityPentaltyFullThreshold(int) - Method in class org.encog.ml.ea.score.adjust.ComplexityAdjustedScore
-
- setConnectionLimit(double) - Method in class org.encog.neural.flat.FlatNetwork
-
- setConstBegin(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setConstDisjoint(double) - Method in class org.encog.neural.neat.training.species.OriginalNEATSpeciation
-
- setConstEnd(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setConstExcess(double) - Method in class org.encog.neural.neat.training.species.OriginalNEATSpeciation
-
- setConstMatched(double) - Method in class org.encog.neural.neat.training.species.OriginalNEATSpeciation
-
- setConstStep(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setContents(String) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Define the structure of the Bayesian network as a string.
- setContextFedBy(FlatLayer) - Method in class org.encog.neural.flat.FlatLayer
-
Set the layer that this layer's context is fed by.
- setContextSource(FreeformNeuron) - Method in class org.encog.neural.freeform.FreeformContextNeuron
-
- setContextTargetOffset(int[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the context target offset.
- setContextTargetSize(int[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the context target size.
- setCount(int) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setCount(int) - Method in class org.encog.ml.data.versatile.division.DataDivision
-
- setCount(int) - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- setCSVFormat(CSVFormat) - Method in class org.encog.util.normalize.DataNormalization
-
Set the CSV format to use.
- setCurrentBlue(int) - Method in class org.encog.util.downsample.RGBDownsample
-
Set the current blue average.
- setCurrentFold(int) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
Set the current fold.
- setCurrentGreen(int) - Method in class org.encog.util.downsample.RGBDownsample
-
Set the current green average.
- setCurrentID(long) - Method in class org.encog.util.identity.BasicGenerateID
-
- setCurrentID(long) - Method in interface org.encog.util.identity.GenerateID
-
- setCurrentLevel(int) - Method in class org.encog.ml.prg.opp.LevelHolder
-
- setCurrentPage(WebPage) - Method in class org.encog.bot.browse.Browser
-
Set the current page.
- setCurrentQuantTask(QuantTask) - Method in class org.encog.app.analyst.EncogAnalyst
-
Set the current task.
- setCurrentRed(int) - Method in class org.encog.util.downsample.RGBDownsample
-
Set the current red average.
- setCurrentState(State) - Method in class org.encog.ml.world.basic.BasicAgent
-
- setCurrentState(State) - Method in interface org.encog.ml.world.WorldAgent
-
- setCurrentState(BiPolarNeuralData) - Method in class org.encog.neural.thermal.ThermalNetwork
-
- setCurrentState(double[]) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Set the current state.
- setCurrentValue(double) - Method in class org.encog.util.normalize.input.BasicInputField
-
Set the current value of this field.
- setCurrentValue(double) - Method in interface org.encog.util.normalize.input.InputField
-
Set the current value of this field.
- setCycles(int) - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- setD1(double) - Method in class org.encog.neural.art.ART1
-
Set the D1 parameter.
- setD1(double) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the D1 parameter.
- setData(double[]) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Set all of the data as an array of doubles.
- setData(ComplexNumber[]) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
- setData(int, double) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Set the data at the specified index.
- setData(int, ComplexNumber) - Method in class org.encog.ml.data.basic.BasicMLComplexData
-
Set a data element to a complex number.
- setData(double[]) - Method in class org.encog.ml.data.basic.BasicMLData
-
Set all of the data as an array of doubles.
- setData(int, double) - Method in class org.encog.ml.data.basic.BasicMLData
-
Set the specified element.
- setData(List<MLDataPair>) - Method in class org.encog.ml.data.basic.BasicMLDataSet
-
- setData(MarketDataType, double) - Method in class org.encog.ml.data.market.loader.LoadedMarketData
-
Set financial data for this date.
- setData(ComplexNumber[]) - Method in interface org.encog.ml.data.MLComplexData
-
- setData(int, ComplexNumber) - Method in interface org.encog.ml.data.MLComplexData
-
Set a data element to a complex number.
- setData(double[]) - Method in interface org.encog.ml.data.MLData
-
Set all of the data as an array of doubles.
- setData(int, double) - Method in interface org.encog.ml.data.MLData
-
Set the specified element.
- setData(double[]) - Method in class org.encog.ml.data.sparse.SparseMLData
-
Set all of the data as an array of doubles.
- setData(int, double) - Method in class org.encog.ml.data.sparse.SparseMLData
-
Set the specified element.
- setData(double[]) - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Store the array.
- setData(int, boolean) - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Set the specified index of this object as a boolean.
- setData(int, double) - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Set the specified index of this object as a double.
- setData(double[]) - Method in class org.encog.ml.data.temporal.TemporalPoint
-
- setData(int, double) - Method in class org.encog.ml.data.temporal.TemporalPoint
-
Set the data at the specified index.
- setData(double[][]) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- setDataset(MatrixMLDataSet) - Method in class org.encog.ml.data.versatile.division.DataDivision
-
- setDataSetSize(int) - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- setDataType(ColumnType) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setDate(Date) - Method in class org.encog.bot.rss.RSSItem
-
Set the publication date.
- setDefaultNormalizedRange(double, double) - Method in class org.encog.app.analyst.script.AnalystScript
-
- setDescription(String) - Method in class org.encog.bot.rss.RSSItem
-
Get the description.
- setDesiredSetSize(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- setDimension(int, int) - Method in class org.encog.mathutil.dimension.MultiDimension
-
Set a single dimension.
- setDuration(double) - Method in class org.encog.ml.schedule.ActionNode
-
- setEarliestStartTime(double) - Method in class org.encog.ml.schedule.ActionNode
-
- setEliteRate(double) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- setEmbedData(boolean) - Method in class org.encog.app.generate.EncogCodeGeneration
-
Set if data should be embeded.
- setEnabled(boolean) - Method in class org.encog.neural.neat.training.NEATLinkGene
-
- setEnd(int) - Method in class org.encog.bot.browse.range.DocumentRange
-
Set the ending index.
- setEndingIndex(int) - Method in class org.encog.app.quant.indicators.Indicator
-
- setEndTraining(int) - Method in class org.encog.neural.flat.FlatNetwork
-
- setError(double) - Method in class org.encog.ml.ea.train.basic.TrainEA
-
Not used.
- setError(double) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- setError(double) - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- setError(double) - Method in class org.encog.ml.train.BasicTraining
-
- setError(double) - Method in interface org.encog.ml.train.MLTrain
-
- setError(double) - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
- setError(Throwable) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- setError(double) - Method in class org.encog.neural.pnn.AbstractPNN
-
- setError(double) - Method in class org.encog.platformspecific.j2se.TrainingDialog
-
Set the current error.
- setErrorFunction(ErrorFunction) - Method in class org.encog.neural.networks.training.propagation.Propagation
-
- setEventType(EventType) - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- setEventValue(BayesianEvent, boolean) - Method in class org.encog.ml.bayesian.query.BasicQuery
-
Set the event value to a boolean.
- setEventValue(BayesianEvent, int) - Method in class org.encog.ml.bayesian.query.BasicQuery
-
Set the event value as a class item.
- setEventValue(BayesianEvent, boolean) - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
Set the event value to a boolean.
- setEventValue(BayesianEvent, int) - Method in interface org.encog.ml.bayesian.query.BayesianQuery
-
Set the event value as a class item.
- setEvidenceSegements(int) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setExclude(int) - Method in class org.encog.neural.pnn.AbstractPNN
-
- setExpectInputHeaders(boolean) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the flag to determine if we are expecting input headers.
- setExtraData(String, Object) - Method in class org.encog.ml.prg.EncogProgram
-
Set extra data that might be needed by extensions.
- setF1Count(int) - Method in class org.encog.neural.art.ART1
-
Set the F1 count.
- setF1Count(int) - Method in class org.encog.neural.bam.BAM
-
Set the F1 neuron count.
- setF1Neurons(int) - Method in class org.encog.neural.pattern.BAMPattern
-
Set the F1 neurons.
- setF2Count(int) - Method in class org.encog.neural.art.ART1
-
Set the F2 count.
- setF2Count(int) - Method in class org.encog.neural.bam.BAM
-
Set the F2 neuron count.
- setF2Neurons(int) - Method in class org.encog.neural.pattern.BAMPattern
-
Set the output neurons.
- setFetchSize(int) - Method in class org.encog.ml.data.buffer.codec.SQLCODEC
-
- setFieldNumber(int) - Method in class org.encog.app.analyst.csv.filter.ExcludedField
-
- setFields(DataField[]) - Method in class org.encog.app.analyst.script.AnalystScript
-
- setFieldValue(String) - Method in class org.encog.app.analyst.csv.filter.ExcludedField
-
- setFile(String) - Method in class org.encog.app.analyst.script.segregate.AnalystSegregateTarget
-
- setFilename(File) - Method in class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
-
- setFilename(String, String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set a filename.
- setFixFlatSopt(boolean) - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Set if we should fix the flat spot problem.
- setFlat(FlatNetwork) - Method in class org.encog.neural.networks.structure.NeuralStructure
-
Set the flat network.
- setFold(int) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setFold(int) - Method in class org.encog.ml.svm.training.SVMTrain
-
Set the number of folds.
- setForceWinner(boolean) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Determine if a winner is to be forced.
- setForDefinition(String) - Method in class org.encog.ml.bayesian.bif.BIFDefinition
-
- setFormat(CSVFormat) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- setFrom(MLData) - Method in class org.encog.neural.networks.NeuralDataMapping
-
Set the from data.
- setFromNeuron(int) - Method in class org.encog.neural.neat.NEATLink
-
Set the from neuron.
- setFromNeuronID(int) - Method in class org.encog.neural.neat.training.NEATLinkGene
-
Set the from neuron id.
- setGamma(double) - Method in class org.encog.ml.svm.training.SVMTrain
-
Set the gamma.
- setGammaBegin(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setGammaEnd(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setGammaStep(double) - Method in class org.encog.ml.svm.training.SVMSearchTrain
-
- setGenerator(PrgGenerator) - Method in class org.encog.ml.prg.opp.SubtreeMutation
-
Set the random tree generator to use.
- setGenetic(MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper) - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
Set the genetic helper class.
- setGenomeFactory(GenomeFactory) - Method in class org.encog.ml.ea.population.BasicPopulation
-
Set the gnome factory.
- setGenomeFactory(GenomeFactory) - Method in interface org.encog.ml.ea.population.Population
-
Set the gnome factory.
- setGensNoImprovement(int) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Set the number of generations with no improvement.
- setGensNoImprovement(int) - Method in interface org.encog.ml.ea.species.Species
-
Set the number of generations with no improvement.
- setGoal(AnalystGoal) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
Set the goal.
- setHasContext(boolean) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the hasContext property.
- setHasRelaxed(boolean) - Method in class org.encog.neural.neat.NEATNetwork
-
Set true, if the network has relaxed and values no longer changing.
- setHigh(double) - Method in class org.encog.engine.network.activation.ActivationRamp
-
Set the high value.
- setHigh(double) - Method in class org.encog.engine.network.activation.ActivationStep
-
Set the high of this function.
- setHigh(int) - Method in class org.encog.mathutil.IntRange
-
Set the high end of the range.
- setHigh(double) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setHighSequence(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- setId(long) - Method in class org.encog.neural.neat.training.NEATBaseGene
-
Set the id for this gene.
- setIdAttribute(String) - Method in class org.encog.bot.browse.range.DocumentRange
-
- setIdeal(boolean) - Method in class org.encog.util.normalize.output.BasicOutputField
-
Set if this is an ideal field.
- setIdeal(boolean) - Method in interface org.encog.util.normalize.output.OutputField
-
Set whether this field is part of the ideal output for a network.
- setIdealArray(double[]) - Method in class org.encog.ml.data.basic.BasicMLDataPair
-
Set the ideal data, the desired output.
- setIdealArray(double[]) - Method in interface org.encog.ml.data.MLDataPair
-
Set the ideal data, the desired output.
- setIgnore(boolean) - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
Set if this column is to be ignored?
- setIgnoreCase(boolean) - Method in class org.encog.util.text.BagOfWords
-
- setImage(Image) - Method in class org.encog.platformspecific.j2se.data.image.ImageMLData
-
- setIncludeTargetField(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setIndentLevel(int) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
- setIndex(int) - Method in class org.encog.app.analyst.csv.basic.FileData
-
Set the index of this field.
- setIndex(int) - Method in class org.encog.app.analyst.csv.sort.SortedField
-
- setIndex(int) - Method in class org.encog.ml.data.temporal.TemporalDataDescription
-
- setIndex(int) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setIndex(int) - Method in class org.encog.util.arrayutil.ClassItem
-
Set the index of the class.
- setInertiaWeight(double) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Set the inertia weight (w)
- setInitialConnectionDensity(double) - Method in class org.encog.neural.neat.NEATPopulation
-
- setInitialPopulation(BasicNetwork[]) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Keep a reference to the passed population of networks.
- setInitialUpdate(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
-
- setInitNetwork(BayesianInit) - Method in class org.encog.ml.bayesian.training.TrainBayesian
-
Set the network init method.
- setInnovationId(long) - Method in class org.encog.neural.neat.training.NEATBaseGene
-
Set the innovation id for this gene.
- setInnovationID(long) - Method in class org.encog.neural.neat.training.NEATInnovation
-
Set the innovation id.
- setInnovations(NEATInnovationList) - Method in class org.encog.neural.neat.NEATPopulation
-
Set the innovation list to use.
- setInput(boolean) - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
Set if this column is used for input.
- setInputArray(double[]) - Method in class org.encog.ml.data.basic.BasicMLDataPair
-
Set the input.
- setInputArray(double[]) - Method in interface org.encog.ml.data.MLDataPair
-
Set the input.
- setInputColumns(List<ColumnDefinition>) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- setInputCount(int) - Method in class org.encog.ml.svm.SVM
-
Set the input count.
- setInputCount(int) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the input count.
- setInputCount(int) - Method in class org.encog.neural.neat.NEATPopulation
-
- setInputCount(int) - Method in class org.encog.neural.neat.training.NEATGenome
-
- setInputData(MLDataSet) - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- setInputFilename(File) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the input filename.
- setInputFormat(CSVFormat) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the input format.
- setInputHeadings(String[]) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the input headings.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.ADALINEPattern
-
Set the input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the input neuron (F1 layer) count.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.BAMPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.CPNPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.ElmanPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.FeedForwardPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.HopfieldPattern
-
Set the number of input neurons, this must match the output neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.JordanPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.PNNPattern
-
Set the input neuron count.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.RadialBasisPattern
-
Set the number of input neurons.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.SOMPattern
-
Set the input neuron count.
- setInputNeurons(int) - Method in class org.encog.neural.pattern.SVMPattern
-
Set the number of input neurons.
- setInputSummation(InputSummation) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Set the input summation method.
- setInputSummation(InputSummation) - Method in interface org.encog.neural.freeform.FreeformNeuron
-
Set the input summation method.
- setInputWindow(int) - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
- setInputWindowSize(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- setInstarCount(int) - Method in class org.encog.neural.pattern.CPNPattern
-
Set the number of neurons in the instar layer.
- setInteger(boolean) - Method in class org.encog.app.analyst.script.DataField
-
- setIteration(int) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the current iteration number.
- setIteration(int) - Method in class org.encog.ml.hmm.train.bw.BaseBaumWelch
-
- setIteration(int) - Method in class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- setIteration(int) - Method in class org.encog.ml.train.BasicTraining
-
- setIteration(int) - Method in interface org.encog.ml.train.MLTrain
-
Set the current training iteration.
- setIteration(int) - Method in class org.encog.neural.freeform.training.FreeformPropagationTraining
-
Set the current training iteration.
- setIterations(int) - Method in class org.encog.platformspecific.j2se.TrainingDialog
-
Set the number of iterations.
- setJobUnit(Object) - Method in class org.encog.util.concurrency.job.JobUnitContext
-
Set the job unit.
- setKernel(PNNKernelType) - Method in class org.encog.neural.pattern.PNNPattern
-
Set the kernel type.
- setKernelType(KernelType) - Method in class org.encog.neural.pattern.SVMPattern
-
Set the kernel type.
- setKfold(int) - Method in class org.encog.app.analyst.commands.Cmd
-
- setL(double) - Method in class org.encog.neural.art.ART1
-
Set the L parameter.
- setL(double) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the L parameter.
- setLagWindowSize(int) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setLagWindowSize(int) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- setLaplaceClasses(int) - Method in class org.encog.util.text.BagOfWords
-
- setLargeArrays(List<double[]>) - Method in class org.encog.persist.EncogFileSection
-
- setLastValue(String) - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- setLatestStartTime(double) - Method in class org.encog.ml.schedule.ActionNode
-
- setLayerBiasActivation(int, double) - Method in class org.encog.neural.networks.BasicNetwork
-
Set the bias activation for the specified layer.
- setLayerContextCount(int[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the layer context count.
- setLayerCounts(int[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the layer counts.
- setLayerFeedCounts(int[]) - Method in class org.encog.neural.flat.FlatNetwork
-
- setLayerIndex(int[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the layer index.
- setLayerOutput(double[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the layer output.
- setLayerSums(double[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the layer sums.
- setLeader(Genome) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Set the leader of this species.
- setLeader(Genome) - Method in interface org.encog.ml.ea.species.Species
-
Set the leader of this species.
- setLeadWindowSize(int) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setLeadWindowSize(int) - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
-
- setLearningRate(double) - Method in class org.encog.ensemble.training.ManhattanPropagationFactory
-
- setLearningRate(double) - Method in class org.encog.neural.cpn.training.TrainInstar
-
Set the learning rate.
- setLearningRate(double) - Method in class org.encog.neural.cpn.training.TrainOutstar
-
Set the learning rate.
- setLearningRate(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
-
- setLearningRate(double) - Method in interface org.encog.neural.networks.training.LearningRate
-
Set the learning rate.
- setLearningRate(double) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
Set the learning rate, this is value is essentially a percent.
- setLearningRate(double) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
-
Set the learning rate.
- setLearningRate(double) - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
Set the learning rate, this is value is essentially a percent.
- setLearningRate(double) - Method in class org.encog.neural.networks.training.simple.TrainAdaline
-
Set the learning rate.
- setLearningRate(double) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Set the learning rate.
- setLen(int) - Method in class org.encog.ml.hmm.alog.KullbackLeiblerDistanceCalculator
-
- setLink(String) - Method in class org.encog.bot.rss.RSSItem
-
Set the hyperlink.
- setLoadToMemory(boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- setLocation(int) - Method in class org.encog.ml.data.buffer.EncogEGBFile
-
Set the current location to the specified row.
- setLogLevel(int) - Method in class org.encog.plugin.system.SystemLoggingPlugin
-
Set the logging level.
- setLow(double) - Method in class org.encog.engine.network.activation.ActivationRamp
-
Set the low value.
- setLow(double) - Method in class org.encog.engine.network.activation.ActivationStep
-
Set the low of this function.
- setLow(int) - Method in class org.encog.mathutil.IntRange
-
Set the low end of the range.
- setLow(double) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setLowSequence(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- setManager(ConcurrentTrainingManager) - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer
-
Set the manager.
- setManager(ConcurrentTrainingManager) - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
-
Set the manager.
- setMatrix(int, int, int, int, Matrix) - Method in class org.encog.mathutil.matrices.Matrix
-
Set a submatrix.
- setMatrix(int, int, int[], Matrix) - Method in class org.encog.mathutil.matrices.Matrix
-
Set a submatrix.
- setMatrix(int[], int, int, Matrix) - Method in class org.encog.mathutil.matrices.Matrix
-
Set a submatrix.
- setMatrix(int[], int[], Matrix) - Method in class org.encog.mathutil.matrices.Matrix
-
Set a submatrix.
- setMax(double) - Method in class org.encog.app.analyst.script.DataField
-
- setMax(double) - Method in class org.encog.util.normalize.input.BasicInputField
-
Set the current max value.
- setMax(double) - Method in interface org.encog.util.normalize.input.InputField
-
Set the current max value.
- setMaxConst(double) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- setMaxError(double) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setMaxError(double) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- setMaxGenerationErrors(int) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- setMaxGenerationErrors(int) - Method in interface org.encog.ml.prg.generator.PrgGenerator
-
Set the maximum errors to allow during generation.
- setMaxIteration(int) - Method in class org.encog.app.analyst.EncogAnalyst
-
Set the max iterations.
- setMaxNumberOfSpecies(int) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- setMaxOperationErrors(int) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- setMaxPosition(double) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Set the boundary of the search space (Xmax)
- setMaxStep(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
-
- setMaxTries(int) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- setMaxVelocity(double) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Sets the maximum velocity.
- setMaxWeight(double) - Method in class org.encog.neural.hyperneat.HyperNEATCODEC
-
- setMean(double) - Method in class org.encog.app.analyst.script.DataField
-
- setMean(double) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setMethod(MLMethod) - Method in class org.encog.app.analyst.EncogAnalyst
-
- setMethod(Form.Method) - Method in class org.encog.bot.browse.range.Form
-
Set the method to send the form.
- setMethod(MLMethod) - Method in class org.encog.ml.data.cross.DataFold
-
- setMethodType(WizardMethodType) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setMin(double) - Method in class org.encog.app.analyst.script.DataField
-
- setMin(double) - Method in class org.encog.util.normalize.input.BasicInputField
-
Set the current min value.
- setMin(double) - Method in interface org.encog.util.normalize.input.InputField
-
Set the current min value.
- setMinConst(double) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- setMinImprovement(double) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- setMinWeight(double) - Method in class org.encog.neural.hyperneat.HyperNEATCODEC
-
- setMissing(HandleMissingValues) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setMissingValues(HandleMissingValues) - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
-
- setMl(MLMethod) - Method in interface org.encog.ensemble.EnsembleML
-
Set the MLMethod to run
- setMl(MLMethod) - Method in class org.encog.ensemble.GenericEnsembleML
-
- setMode(ErrorCalculationMode) - Static method in class org.encog.mathutil.error.ErrorCalculation
-
Set the error calculation mode, this is static and therefore global to
all Enocg training.
- setModel(svm_model) - Method in class org.encog.ml.svm.SVM
-
Set the model.
- setMomentum(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
-
- setMomentum(double) - Method in interface org.encog.neural.networks.training.Momentum
-
Set the momentum.
- setMomentum(double) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
-
Set the momentum for training.
- setNaiveBayes(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setName(String) - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
Set the name of this column.
- setName(String) - Method in class org.encog.app.analyst.script.AnalystClassItem
-
- setName(String) - Method in class org.encog.app.analyst.script.DataField
-
- setName(String) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Set the name of the field.
- setName(String) - Method in class org.encog.app.analyst.script.task.AnalystTask
-
- setName(String) - Method in class org.encog.bot.browse.range.FormElement
-
Set the name of this form element.
- setName(String) - Method in class org.encog.ml.bayesian.bif.BIFVariable
-
- setName(String) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setName(String) - Method in class org.encog.ml.ea.population.BasicPopulation
-
Set the name.
- setName(String) - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- setName(String) - Method in class org.encog.parse.tags.Tag
-
Set the tag name.
- setName(String) - Method in class org.encog.util.arrayutil.ClassItem
-
Set the name of the class.
- setName(String) - Method in class org.encog.util.arrayutil.NormalizedField
-
Set the name of the field.
- setName(String) - Method in class org.encog.util.arrayutil.TemporalWindowField
-
- setNEATActivationFunction(ActivationFunction) - Method in class org.encog.neural.neat.NEATPopulation
-
Specify to use a single activation function.
- setNetwork(BasicNetwork) - Method in class org.encog.neural.networks.layers.BasicLayer
-
Set the network for this layer.
- setNetwork(BasicNetwork) - Method in interface org.encog.neural.networks.layers.Layer
-
Set the network that this layer belongs to.
- setNetwork(BasicNetwork) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- setNetworkDepth(int) - Method in class org.encog.neural.neat.training.NEATGenome
-
- setNetworkState(int, double[]) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Sets the state of the networks in the swarm
- setNeuronCount(int) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Set the neuron count.
- setNeuronID(long) - Method in class org.encog.neural.neat.training.NEATInnovation
-
Set the neuron id.
- setNeuronType(NEATNeuronType) - Method in class org.encog.neural.neat.training.NEATNeuronGene
-
Set the neuron type.
- setNodeCount(int) - Method in class org.encog.ml.tree.traverse.tasks.TaskCountNodes
-
Set the current node count.
- setNodeFound(ProgramNode) - Method in class org.encog.ml.prg.opp.LevelHolder
-
- setNormalizationEnabled(boolean) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- setNormalizedHigh(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Set the normalized high for the field.
- setNormalizedHigh(double) - Method in class org.encog.util.arrayutil.NormalizeArray
-
Set the high value to normalize to.
- setNormalizedHigh(double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Set the normalized high for the field.
- setNormalizedLow(double) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Set the normalized low for the field.
- setNormalizedLow(double) - Method in class org.encog.util.arrayutil.NormalizeArray
-
Set the low value to normalize to.
- setNormalizedLow(double) - Method in class org.encog.util.arrayutil.NormalizedField
-
Set the normalized low for the field.
- setNormalizedMax(float) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- setNormalizedMin(float) - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- setNormHelper(NormalizationHelper) - Method in class org.encog.ml.data.versatile.VersatileMLDataSet
-
- setNormStrategy(NormalizationStrategy) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- setNoWinner(int) - Method in class org.encog.neural.art.ART1
-
Set the i parameter.
- setNumberRemaining(int) - Method in class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
-
- setNumGensAllowedNoImprovement(int) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- setNumSigmas(int) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- setOffset(int) - Method in class org.encog.util.normalize.input.InputFieldEncogCollection
-
- setOffspringCount(int) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Set the offspring count.
- setOffspringCount(int) - Method in interface org.encog.ml.ea.species.Species
-
Set the offspring count.
- setOptions(List<String>) - Method in class org.encog.ml.bayesian.bif.BIFVariable
-
- setOutmodel(PNNOutputMode) - Method in class org.encog.neural.pattern.PNNPattern
-
Set the output model.
- setOutput(boolean) - Method in class org.encog.app.analyst.csv.basic.BaseCachedColumn
-
Set if this column is used for output.
- setOutput(boolean) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
Set if this is an output field.
- setOutputColumns(List<ColumnDefinition>) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- setOutputCount(int) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the output count.
- setOutputCount(int) - Method in class org.encog.neural.neat.NEATPopulation
-
- setOutputCount(int) - Method in class org.encog.neural.neat.training.NEATGenome
-
- setOutputEpsilon(double) - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
- setOutputNeuron(int) - Method in class org.encog.mathutil.matrices.hessian.ChainRuleWorker
-
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.ADALINEPattern
-
Set the output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the output neuron (F2 layer) count.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.BAMPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.CPNPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.ElmanPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.FeedForwardPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.HopfieldPattern
-
Set the number of output neurons, should not be used with a hopfield
neural network, because the number of input neurons defines the number of
output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.JordanPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.PNNPattern
-
Set the output neuron count.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.RadialBasisPattern
-
Set the number of output neurons.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.SOMPattern
-
Set the output neuron count.
- setOutputNeurons(int) - Method in class org.encog.neural.pattern.SVMPattern
-
Set the number of output neurons.
- setOutstarCount(int) - Method in class org.encog.neural.pattern.CPNPattern
-
Set the number of neurons in the outstar level, this level is mapped to
the "output" level.
- setOwner(Form) - Method in class org.encog.bot.browse.range.FormElement
-
Set the owner of this form element.
- setOwner(BufferedMLDataSet) - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
Set the owner of this dataset.
- setOwner(FoldedDataSet) - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- setOwner(NormalizationHelper) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
Set the owner of this class.
- setOwner(ConcurrentJob) - Method in class org.encog.util.concurrency.job.JobUnitContext
-
Set the job owner.
- setPair(MLDataPair) - Method in class org.encog.util.normalize.input.MLDataFieldHolder
-
Set the pair.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationBiPolar
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationClippedLinear
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationCompetitive
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationElliott
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationElliottSymmetric
-
Set one of the params for this activation function.
- setParam(int, double) - Method in interface org.encog.engine.network.activation.ActivationFunction
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationGaussian
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationLinear
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationLOG
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationRamp
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationSigmoid
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationSIN
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationSoftMax
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationSteepenedSigmoid
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationStep
-
Set one of the params for this activation function.
- setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationTANH
-
Set one of the params for this activation function.
- setParameters(Collection<Integer>, ActivationFunction) - Method in class org.encog.ensemble.ml.mlp.factory.MultiLayerPerceptronFactory
-
- setParams(double, double) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Set the learning rate and radius.
- setParent(DocumentRange) - Method in class org.encog.bot.browse.range.DocumentRange
-
Set the parent.
- setPassThrough(boolean) - Method in class org.encog.ml.prg.extension.ParamTemplate
-
- setPeak(double) - Method in class org.encog.mathutil.rbf.BasicRBF
-
Set the peak.
- setPeak(double) - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
Set the peak.
- setPercent(int) - Method in class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
-
- setPercent(int) - Method in class org.encog.app.analyst.script.segregate.AnalystSegregateTarget
-
- setPercision(int) - Method in class org.encog.app.quant.loader.yahoo.YahooDownload
-
- setPercision(int) - Method in class org.encog.app.quant.ninja.NinjaStreamWriter
-
Set the percision to use.
- setPhenotype(MLEncodable) - Method in class org.encog.ml.genetic.MLMethodGenome
-
- setPhysics(double[]) - Method in class org.encog.ca.program.generic.GenericCA
-
- setPi(int, double) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- setPi(double[]) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- setPixelMap(int[]) - Method in class org.encog.util.downsample.RGBDownsample
-
Set the pixel map.
- setPointsPerSide(int) - Method in class org.encog.mathutil.matrices.hessian.HessianFD
-
This specifies the number of points per side, default is 5.
- setPolicyValue(State, Action, double) - Method in class org.encog.ml.world.basic.BasicWorld
-
- setPolicyValue(State, Action, double) - Method in interface org.encog.ml.world.World
-
- setPolicyValueSize(int) - Method in class org.encog.ml.world.basic.BasicState
-
- setPolicyValueSize(int) - Method in interface org.encog.ml.world.State
-
- setPopulation(Population) - Method in class org.encog.ml.ea.genome.BasicGenome
-
- setPopulation(Population) - Method in interface org.encog.ml.ea.genome.Genome
-
Set the population that this genome belongs to.
- setPopulation(Population) - Method in class org.encog.ml.ea.species.BasicSpecies
-
Set the population.
- setPopulation(Population) - Method in interface org.encog.ml.ea.species.Species
-
Set the population.
- setPopulation(Population) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the population.
- setPopulation(Population) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Set the population.
- setPopulation(NEATPopulation) - Method in class org.encog.neural.neat.training.NEATInnovationList
-
Set the population that this genome belongs to.
- setPopulationSize(int) - Method in class org.encog.ml.ea.population.BasicPopulation
-
Set the max population size.
- setPopulationSize(int) - Method in interface org.encog.ml.ea.population.Population
-
Set the max population size.
- setPopulationSize(int) - Method in class org.encog.neural.networks.training.pso.NeuralPSO
-
Set the swarm size.
- setPrecision(int) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the precision to use.
- setPredictWindow(int) - Method in class org.encog.util.arrayutil.TemporalWindowArray
-
- setPredictWindowSize(int) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- setPreprocess(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setProbability(double) - Method in class org.encog.ml.bayesian.table.TableLine
-
Set the probability of this line.
- setProbability(ActionProbability) - Method in class org.encog.ml.world.basic.BasicWorld
-
- setProbability(ActionProbability) - Method in interface org.encog.ml.world.World
-
- setProbabilityLeft(double) - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- setProbabilityReverse(double) - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- setProbabilityRight(double) - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- setProbabilitySame(double) - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- setProbabilitySuccess(double) - Method in class org.encog.ml.world.grid.probability.GridStochasticProbability
-
- setProduceOutputHeaders(boolean) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- setProgram(EncogGenProgram) - Method in class org.encog.app.generate.program.EncogTreeNode
-
Set the program.
- setProperty(String, AnalystFileFormat) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set the property to a format.
- setProperty(String, AnalystGoal) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set a property.
- setProperty(String, boolean) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set a property as a boolean.
- setProperty(String, double) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set a property as a double.
- setProperty(String, File) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as an object.
- setProperty(String, int) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set a property to an int.
- setProperty(String, String) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set the property to the specified value.
- setProperty(String, URL) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Get a property as an object.
- setProperty(String, TargetLanguage) - Method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Set a property as a target language.
- setProperty(String, double) - Method in class org.encog.ml.BasicML
-
Set a property as a double.
- setProperty(String, long) - Method in class org.encog.ml.BasicML
-
Set a property as a long.
- setProperty(String, String) - Method in class org.encog.ml.BasicML
-
Set a property as a double.
- setProperty(String, double) - Method in interface org.encog.ml.MLProperties
-
Set a property as a double.
- setProperty(String, long) - Method in interface org.encog.ml.MLProperties
-
Set a property as a long.
- setProperty(String, String) - Method in interface org.encog.ml.MLProperties
-
Set a property as a double.
- setProperty(String, Object) - Method in class org.encog.ml.world.basic.BasicState
-
- setProperty(String, Object) - Method in interface org.encog.ml.world.State
-
- setQuery(BayesianQuery) - Method in class org.encog.ml.bayesian.BayesianNetwork
-
- setRadius(double) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodBubble
-
Set the radius.
- setRadius(double) - Method in interface org.encog.neural.som.training.basic.neighborhood.NeighborhoodFunction
-
Set the radius.
- setRadius(double) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF
-
Set the radius.
- setRadius(double) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF1D
-
Set the radius.
- setRadius(double) - Method in class org.encog.neural.som.training.basic.neighborhood.NeighborhoodSingle
-
Set the radius.
- setRandom(GenerateRandom) - Method in class org.encog.mathutil.randomize.BasicRandomizer
-
- setRandom(GenerateRandom) - Method in interface org.encog.mathutil.randomize.Randomizer
-
Explicitly set the Random source
- setRandomFactory(RandomFactory) - Method in class org.encog.Encog
-
- setRandomFactory(RandomFactory) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- setRandomNumberFactory(RandomFactory) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- setRandomNumberFactory(RandomFactory) - Method in class org.encog.neural.neat.NEATPopulation
-
- setRange(NormalizeRange) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setRBF(RadialBasisFunction[]) - Method in class org.encog.neural.flat.FlatNetworkRBF
-
Set the RBF's used.
- setRBF(RBFEnum) - Method in class org.encog.neural.pattern.RadialBasisPattern
-
- setRBF(RadialBasisFunction[]) - Method in class org.encog.neural.rbf.RBFNetwork
-
Set the RBF's.
- setRBFCentersAndWidths(double[][], double[], RBFEnum) - Method in class org.encog.neural.rbf.RBFNetwork
-
Array containing center position.
- setRBFCentersAndWidthsEqualSpacing(double, double, RBFEnum, double, boolean) - Method in class org.encog.neural.rbf.RBFNetwork
-
Equally spaces all hidden neurons within the n dimensional variable
space.
- setRBFFunction(int, RBFEnum, double[], double) - Method in class org.encog.neural.rbf.RBFNetwork
-
Set an RBF function.
- setReal(boolean) - Method in class org.encog.app.analyst.script.DataField
-
- setRecordCount(int) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the record count.
- setRecurrent(boolean) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Determine if this is a recurrent connecton.
- setRecurrent(boolean) - Method in interface org.encog.neural.freeform.FreeformConnection
-
Determine if this is a recurrent connecton.
- setRegression(boolean) - Method in class org.encog.neural.pattern.SVMPattern
-
Set if regression is used.
- setRelaxationThreshold(double) - Method in class org.encog.neural.neat.NEATNetwork
-
The amount of change allowed before the network is considered to have
relaxed.
- setReport(StatusReportable) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the status reporting object.
- setReport(StatusReportable) - Method in class org.encog.ml.model.EncogModel
-
- setReport(StatusReportable) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Setup the object to report status to.
- setReport(StatusReportable) - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
- setReport(StatusReportable) - Method in class org.encog.util.normalize.DataNormalization
-
Set the object that this one is reporting to.
- setReportInterval(int) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Set the reporting interval.
- setResourceName(String) - Method in class org.encog.util.normalize.input.InputFieldEncogCollection
-
- setResourceName(String) - Method in class org.encog.util.normalize.target.NormalizationStorageEncogCollection
-
- setResult(BasicMLDataSet) - Method in class org.encog.ml.data.buffer.MemoryDataLoader
-
Set the resulting dataset.
- setResult(VariableMapping) - Method in class org.encog.ml.prg.EncogProgramContext
-
- setReward(double) - Method in class org.encog.ml.world.basic.BasicState
-
- setReward(double) - Method in interface org.encog.ml.world.State
-
- setRnd(GenerateRandom) - Method in class org.encog.ml.data.cross.KFoldCrossvalidation
-
- setRootNode(ProgramNode) - Method in class org.encog.ml.prg.EncogProgram
-
Set the root node for the program.
- setRounds(int) - Method in class org.encog.ml.ea.opp.selection.TournamentSelection
-
Set the number of rounds.
- setRPROPType(RPROPType) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
-
Set the type of RPROP to use.
- setRules(RuleHolder) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
- setRules(RuleHolder) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Set the rules holder to use.
- setRunCycles(int) - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Set the number of cycles per run.
- setRunCycles(int) - Method in class org.encog.neural.thermal.BoltzmannMachine
-
- setSamples(BasicMLDataSet) - Method in class org.encog.neural.pnn.BasicPNN
-
- setSampleSize(int) - Method in class org.encog.ml.bayesian.query.sample.SamplingQuery
-
- setScore(double) - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Set the score.
- setScore(double) - Method in class org.encog.ml.data.cross.DataFold
-
- setScore(double) - Method in class org.encog.ml.ea.genome.BasicGenome
-
Set the score.
- setScore(double) - Method in interface org.encog.ml.ea.genome.Genome
-
Set the score.
- setScore(CalculateScore) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- setScript(AnalystScript) - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- setScript(AnalystScript) - Method in class org.encog.app.analyst.script.preprocess.AnalystPreprocess
-
- setSd(double) - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
-
- setSeed(long) - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- setSeed(int[]) - Method in class org.encog.mathutil.randomize.generate.MersenneTwisterGenerateRandom
-
- setSegregateTargets(AnalystSegregateTarget[]) - Method in class org.encog.app.analyst.script.segregate.AnalystSegregate
-
- setSelection(SelectionOperator) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the selection operator.
- setSelection(SelectionOperator) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Set the selection operator.
- setSelectionComparator(GenomeComparator) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the comparator that is used to choose the "best" genome for
selection, as opposed to the "true best".
- setSelectionComparator(GenomeComparator) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Set the comparator that is used to choose the "best" genome for
selection, as opposed to the "true best".
- setSeparateClass(boolean) - Method in class org.encog.neural.pnn.AbstractPNN
-
- setSequence(int) - Method in class org.encog.ml.data.temporal.TemporalPoint
-
- setSequenceCount(int) - Method in class org.encog.ml.hmm.alog.KullbackLeiblerDistanceCalculator
-
- setSequenceGrandularity(TimeUnit) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- setShouldIgnoreExceptions(boolean) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Determines if genetic operator exceptions should be ignored.
- setShouldIgnoreExceptions(boolean) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Determines if genetic operator exceptions should be ignored.
- setShouldMinimize(boolean) - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
Should the score be minimized.
- setShrink(double) - Method in class org.encog.neural.networks.training.propagation.quick.QuickPropagation
-
- setSigmaHigh(double) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- setSigmaLow(double) - Method in class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
- setSignificance(ArrayList<Double>) - Method in class org.encog.ensemble.data.factories.EnsembleDataSetFactory
-
- setSignificance(double) - Method in class org.encog.ml.data.basic.BasicMLDataPair
-
Set the significance, 1.0 is neutral.
- setSignificance(double) - Method in interface org.encog.ml.data.MLDataPair
-
Set the significance, 1.0 is neutral.
- setSingleThreaded(boolean) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
- setSortGenomes(SortGenomesForSpecies) - Method in class org.encog.ml.ea.species.ThresholdSpeciation
-
- setSortType(SortType) - Method in class org.encog.app.analyst.csv.sort.SortedField
-
- setSource(String) - Method in class org.encog.app.analyst.script.DataField
-
- setSource(WebPage) - Method in class org.encog.bot.browse.range.DocumentRange
-
Set the source web page.
- setSource(FreeformNeuron) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Set the source neuron.
- setSource(FreeformNeuron) - Method in interface org.encog.neural.freeform.FreeformConnection
-
Set the source neuron.
- setSourceColumns(List<ColumnDefinition>) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
- setSourceFile(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.normalize.AnalystNormalizeCSV
-
Set the source file.
- setSourceFile(File, boolean, CSVFormat) - Method in class org.encog.app.analyst.csv.normalize.AnalystNormalizeToEGB
-
Set the source file.
- setSourceUniverse(Universe) - Method in interface org.encog.ca.program.CAProgram
-
- setSourceUniverse(Universe) - Method in class org.encog.ca.program.conway.ConwayProgram
-
- setSourceUniverse(Universe) - Method in class org.encog.ca.program.elementary.ElementaryCA
-
- setSourceUniverse(Universe) - Method in class org.encog.ca.program.generic.GenericCA
-
- setSpeciation(Speciation) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the speciation method.
- setSpeciation(Speciation) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Set the speciation method.
- setSpecies(Species) - Method in class org.encog.ml.ea.genome.BasicGenome
-
- setSpecies(Species) - Method in interface org.encog.ml.ea.genome.Genome
-
Set the species for this genome.
- setStandardDeviation(double) - Method in class org.encog.app.analyst.script.DataField
-
- setStartingPoint(Date) - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
- setStartTemperature(double) - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- setStateDistribution(int, StateDistribution) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- setStatus(StatusReportable) - Method in class org.encog.ml.data.buffer.BinaryDataLoader
-
Set the object that status is reported to.
- setStatus(StatusReportable) - Method in class org.encog.ml.data.buffer.MemoryDataLoader
-
Set the object that status will be reported to.
- setStopTemperature(double) - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- setStrategy(NormalizationStrategy) - Method in class org.encog.ml.data.versatile.NormalizationHelper
-
Set the normalization strategy.
- setSubstrate(Substrate) - Method in class org.encog.neural.neat.NEATPopulation
-
- setSurvivalRate(double) - Method in class org.encog.neural.neat.NEATPopulation
-
Set the survival rate, this is the percent of the population allowed to mate.
- setSVMType(SVMType) - Method in class org.encog.neural.pattern.SVMPattern
-
Set the SVM type.
- setTable(String) - Method in class org.encog.ml.bayesian.bif.BIFDefinition
-
- setTag(Tag) - Method in class org.encog.bot.dataunit.TagDataUnit
-
Set the tag that this data unit is based on.
- setTarget(Address) - Method in class org.encog.bot.browse.range.Link
-
Set the target of this link.
- setTarget(FreeformNeuron) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Set the target neuron.
- setTarget(FreeformNeuron) - Method in interface org.encog.neural.freeform.FreeformConnection
-
Set the target neuron.
- setTarget(NormalizationStorage) - Method in class org.encog.util.normalize.DataNormalization
-
Determines where the normalized data will be sent.
- setTargetField(AnalystField) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
Set the target field.
- setTargetField(String) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setTargetUniverse(Universe) - Method in interface org.encog.ca.program.CAProgram
-
- setTargetUniverse(Universe) - Method in class org.encog.ca.program.conway.ConwayProgram
-
- setTargetUniverse(Universe) - Method in class org.encog.ca.program.elementary.ElementaryCA
-
- setTargetUniverse(Universe) - Method in class org.encog.ca.program.generic.GenericCA
-
- setTaskBalance(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setTaskCluster(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setTaskNormalize(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setTaskNumber(int) - Method in class org.encog.util.concurrency.job.JobUnitContext
-
Set the task number.
- setTaskRandomize(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setTaskSegregate(boolean) - Method in class org.encog.app.analyst.wizard.AnalystWizard
-
- setTemperature(double) - Method in class org.encog.ml.anneal.SimulatedAnnealing
-
- setTemperature(double) - Method in class org.encog.neural.pattern.BoltzmannPattern
-
Set the temperature.
- setTemperature(double) - Method in class org.encog.neural.thermal.BoltzmannMachine
-
Set the network temperature.
- setTempTraining(int, double) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Set a temp training value.
- setTempTraining(int, double) - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
-
Set a temp training value.
- setTempTraining(int, double) - Method in interface org.encog.neural.freeform.TempTrainingData
-
Set a temp training value.
- setText(String) - Method in class org.encog.bot.dataunit.TextDataUnit
-
Set the text for this data unit.
- setThreadCount(int) - Method in class org.encog.mathutil.matrices.hessian.HessianCR
-
Set the number of threads.
- setThreadCount(int) - Method in class org.encog.ml.ea.score.parallel.ParallelScore
-
- setThreadCount(int) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Set the number of threads to use.
- setThreadCount(int) - Method in class org.encog.ml.genetic.MLMethodGeneticAlgorithm
-
- setThreadCount(int) - Method in class org.encog.ml.prg.generator.AbstractPrgGenerator
-
- setThreadCount(int) - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
-
- setThreadCount(int) - Method in class org.encog.neural.networks.training.propagation.Propagation
-
Set the number of threads.
- setThreadCount(int) - Method in class org.encog.util.concurrency.EngineConcurrency
-
Set the number of threads to use.
- setThreadCount(int) - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
Set the number of threads to use.
- setThreadCount(int) - Method in interface org.encog.util.concurrency.MultiThreadable
-
Set the number of threads to use.
- setThreshold(double[]) - Method in class org.encog.neural.thermal.BoltzmannMachine
-
Set the thresholds.
- setThresholdHigh(double) - Method in class org.encog.engine.network.activation.ActivationRamp
-
Set the threshold high.
- setThresholdLow(double) - Method in class org.encog.engine.network.activation.ActivationRamp
-
Set the threshold low.
- setTime(int) - Method in class org.encog.platformspecific.j2se.TrainingDialog
-
Set the time.
- setTimeSlice(int) - Method in class org.encog.app.analyst.script.normalize.AnalystField
-
- setTitle(DocumentRange) - Method in class org.encog.bot.browse.WebPage
-
Set the title of this document.
- setTitle(String) - Method in class org.encog.bot.rss.RSSItem
-
Set the item title.
- setTo(MLData) - Method in class org.encog.neural.networks.NeuralDataMapping
-
Set the target data.
- setToNeuron(int) - Method in class org.encog.neural.neat.NEATLink
-
Set the target neuron.
- setToNeuronID(int) - Method in class org.encog.neural.neat.training.NEATLinkGene
-
Set the to neuron id.
- setTotalWords(int) - Method in class org.encog.util.text.BagOfWords
-
- setTrain(MLTrain) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- setTrained(boolean) - Method in class org.encog.neural.pnn.AbstractPNN
-
- setTrainer(EvolutionaryAlgorithm) - Method in class org.encog.ml.ea.opp.selection.TournamentSelection
-
Set the trainer.
- setTraining(MLTrain) - Method in interface org.encog.ensemble.EnsembleML
-
Set the training for this member
- setTraining(MLTrain) - Method in class org.encog.ensemble.GenericEnsembleML
-
- setTraining(MLDataSet) - Method in class org.encog.ml.train.BasicTraining
-
Set the training object that this strategy is working with.
- setTraining(MLDataSet) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- setTrainingData(MLDataSet) - Method in class org.encog.ensemble.Ensemble
-
Set which training data to base the training on
- setTrainingDataFactory(EnsembleDataSetFactory) - Method in class org.encog.ensemble.Ensemble
-
Set which dataSetFactory to use to create the correct tranining sets
- setTrainingDataset(MatrixMLDataSet) - Method in class org.encog.ml.model.EncogModel
-
- setTrainingMethod(EnsembleTrainFactory) - Method in class org.encog.ensemble.Ensemble
-
Set the training method to use for this ensemble
- setTrainingSet(EnsembleDataSet) - Method in class org.encog.ensemble.aggregator.Averaging
-
- setTrainingSet(EnsembleDataSet) - Method in class org.encog.ensemble.aggregator.MajorityVoting
-
- setTrainingSet(EnsembleDataSet) - Method in class org.encog.ensemble.aggregator.MetaClassifier
-
- setTrainingSet(EnsembleDataSet) - Method in interface org.encog.ensemble.EnsembleAggregator
-
- setTrainingSet(EnsembleDataSet) - Method in interface org.encog.ensemble.EnsembleML
-
Set the dataset for this member
- setTrainingSet(EnsembleDataSet) - Method in class org.encog.ensemble.GenericEnsembleML
-
- setTrainingType(String) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
-
- setTransitionProbability(int, int, double) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- setTransitionProbability(double[][]) - Method in class org.encog.ml.hmm.HiddenMarkovModel
-
- setType(String) - Method in class org.encog.bot.browse.range.Input
-
Set the type of this input element.
- setType(Tag.Type) - Method in class org.encog.parse.tags.Tag
-
Set the tag type.
- setTypes(List<ValueType>) - Method in class org.encog.ml.prg.opp.LevelHolder
-
- SETUP_CONFIG_ALLOWED_CLASSES - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: = "SETUP:CONFIG_allowedClasses".
- SETUP_CONFIG_CSV_FORMAT - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "SETUP:CONFIG_csvFormat".
- SETUP_CONFIG_INPUT_HEADERS - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "SETUP:CONFIG_inputHeaders".
- SETUP_CONFIG_MAX_CLASS_COUNT - Static variable in class org.encog.app.analyst.script.prop.ScriptProperties
-
Property for: "SETUP:CONFIG_maxClassCount".
- setUsedDefault(boolean) - Method in class org.encog.ml.factory.parse.ArchitectureLayer
-
- setUsedForNetworkInput(boolean) - Method in class org.encog.util.normalize.input.BasicInputField
-
This is needed so that the buildForNetworkInput method of the
normalization class knows how many input fields to expect.
- setValidationDataset(MatrixMLDataSet) - Method in class org.encog.ml.model.EncogModel
-
- setValidationMode(boolean) - Method in class org.encog.ml.ea.train.basic.BasicEA
-
Determine if the genomes should be validated.
- setValidationMode(boolean) - Method in interface org.encog.ml.ea.train.EvolutionaryAlgorithm
-
Determine if the genomes should be validated.
- setValue(String) - Method in class org.encog.bot.browse.range.FormElement
-
Set the value for this form element.
- setValue(String) - Method in class org.encog.ml.bayesian.parse.ParsedEvent
-
Set the value for this event.
- setValue(int) - Method in class org.encog.ml.bayesian.query.sample.EventState
-
- setVariable(int, double) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Set a variable floating point value by index.
- setVariable(String, double) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Set a floating point variable value by name.
- setVariable(String, ExpressionValue) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Set a variable value by name.
- setVigilance(double) - Method in class org.encog.neural.art.ART1
-
Set the vigilance.
- setVigilance(double) - Method in class org.encog.neural.pattern.ART1Pattern
-
Set the vigilance for the network.
- setVisited(int) - Method in class org.encog.ml.world.basic.BasicState
-
- setVisited(int) - Method in interface org.encog.ml.world.State
-
- setWeight(double) - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
-
Set the weight.
- setWeight(double) - Method in interface org.encog.neural.freeform.FreeformConnection
-
Set the weight.
- setWeight(double) - Method in class org.encog.neural.neat.NEATLink
-
Set the weight of this link.
- setWeight(double) - Method in class org.encog.neural.neat.training.NEATLinkGene
-
Set the weight of this connection.
- setWeight(int, int, int, double) - Method in class org.encog.neural.networks.BasicNetwork
-
Set the weight between the two specified neurons.
- setWeight(int, int, double) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Set the weight.
- setWeightIndex(int[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the weight index.
- setWeights(double[]) - Method in class org.encog.neural.flat.FlatNetwork
-
Set the weights.
- setWeights(Matrix) - Method in class org.encog.neural.som.SOM
-
- setWeights(double[]) - Method in class org.encog.neural.thermal.ThermalNetwork
-
Set the weight array.
- setWeightsF1toF2(Matrix) - Method in class org.encog.neural.art.ART1
-
Set the f1 to f2 matrix.
- setWeightsF1toF2(Matrix) - Method in class org.encog.neural.bam.BAM
-
Set the weights for F1 to F2.
- setWeightsF2toF1(Matrix) - Method in class org.encog.neural.art.ART1
-
Set the f2 to f1 matrix.
- setWeightsF2toF1(Matrix) - Method in class org.encog.neural.bam.BAM
-
Set the weights for F2 to F1.
- setWidth(double) - Method in class org.encog.mathutil.rbf.BasicRBF
-
Set the width.
- setWidth(double) - Method in interface org.encog.mathutil.rbf.RadialBasisFunction
-
Set the width.
- setWorld(World) - Method in class org.encog.ml.world.basic.BasicAgent
-
- setWorld(World) - Method in interface org.encog.ml.world.WorldAgent
-
- setX(int) - Method in class org.encog.mathutil.IntPair
-
- setX1(double) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- setX2(double) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- setX3(double) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- setY(int) - Method in class org.encog.mathutil.IntPair
-
- setY1(double) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- setY2(double) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- setY3(double) - Method in class org.encog.neural.networks.training.pnn.GlobalMinimumSearch
-
- setZoom(int) - Method in class org.encog.ca.visualize.basic.BasicCAVisualizer
-
- setZoom(int) - Method in interface org.encog.ca.visualize.CAVisualizer
-
- shift() - Method in class org.encog.util.datastruct.WindowInt
-
- shouldContinue() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
- shouldInclude() - Method in class org.encog.util.normalize.segregate.index.IndexRangeSegregator
-
Determines if the current row should be included.
- shouldInclude() - Method in class org.encog.util.normalize.segregate.index.IndexSampleSegregator
-
Should this row be included.
- shouldInclude() - Method in class org.encog.util.normalize.segregate.IntegerBalanceSegregator
-
Determine of the current row should be included.
- shouldInclude() - Method in class org.encog.util.normalize.segregate.RangeSegregator
-
- shouldInclude() - Method in interface org.encog.util.normalize.segregate.Segregator
-
Should this row be included, according to this segregator.
- shouldMinimize() - Method in interface org.encog.ml.CalculateScore
-
- shouldMinimize() - Method in class org.encog.ml.ea.score.EmptyScoreFunction
- shouldMinimize() - Method in interface org.encog.ml.ea.sort.GenomeComparator
-
- shouldMinimize() - Method in class org.encog.ml.ea.sort.MaximizeAdjustedScoreComp
- shouldMinimize() - Method in class org.encog.ml.ea.sort.MaximizeScoreComp
- shouldMinimize() - Method in class org.encog.ml.ea.sort.MinimizeAdjustedScoreComp
- shouldMinimize() - Method in class org.encog.ml.ea.sort.MinimizeScoreComp
- shouldMinimize() - Method in class org.encog.ml.fitness.MultiObjectiveFitness
- shouldMinimize() - Method in class org.encog.ml.prg.train.ZeroEvalScoreFunction
- shouldMinimize() - Method in class org.encog.neural.networks.training.TrainingSetScore
-
A training set based score should always seek to lower the error,
as a result, this method always returns true.
- shouldShutDown() - Method in interface org.encog.app.analyst.AnalystListener
-
- shouldShutDown() - Method in class org.encog.app.analyst.ConsoleAnalystListener
- shouldStop() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
- shouldStop() - Method in class org.encog.app.quant.loader.yahoo.YahooDownload
-
- shouldStop() - Method in interface org.encog.app.quant.QuantTask
-
- shouldStop() - Method in class org.encog.ml.train.strategy.end.EarlyStoppingStrategy
-
- shouldStop() - Method in class org.encog.ml.train.strategy.end.EndIterationsStrategy
- shouldStop() - Method in class org.encog.ml.train.strategy.end.EndMaxErrorStrategy
- shouldStop() - Method in class org.encog.ml.train.strategy.end.EndMinutesStrategy
- shouldStop() - Method in interface org.encog.ml.train.strategy.end.EndTrainingStrategy
-
- shouldStop() - Method in class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
- shouldStop() - Method in class org.encog.ml.train.strategy.StopTrainingStrategy
- shouldStop() - Method in class org.encog.platformspecific.j2se.TrainingDialog
-
- shouldStopCommand() - Method in interface org.encog.app.analyst.AnalystListener
-
- shouldStopCommand() - Method in class org.encog.app.analyst.ConsoleAnalystListener
- shouldStopCommand() - Method in class org.encog.app.analyst.EncogAnalyst
-
Should the current command be stopped.
- shrinking - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- ShuffleCSV - Class in org.encog.app.analyst.csv.shuffle
-
Randomly shuffle the lines of a CSV file.
- ShuffleCSV() - Constructor for class org.encog.app.analyst.csv.shuffle.ShuffleCSV
-
Construct the object.
- shutdown() - Method in class org.encog.Encog
-
Provides any shutdown that Encog may need.
- shutdown(long) - Method in class org.encog.util.concurrency.EngineConcurrency
-
Wait for all threads in the pool to complete.
- SIGMA - Static variable in class org.encog.persist.PersistConst
-
Sigma.
- SIGMOID - Static variable in class org.encog.mathutil.libsvm.svm_parameter
-
- sign(double) - Static method in class org.encog.mathutil.EncogMath
-
Determine the sign of the value.
- SIGN(double, double) - Static method in class org.encog.neural.rbf.training.SVD
-
- SimpleDestinationGoal - Class in org.encog.ml.graph.search
-
- SimpleDestinationGoal(BasicNode) - Constructor for class org.encog.ml.graph.search.SimpleDestinationGoal
-
- SimpleEarlyStoppingStrategy - Class in org.encog.ml.train.strategy.end
-
A simple early stopping strategy that halts training when the validation set no longer improves.
- SimpleEarlyStoppingStrategy(MLDataSet) - Constructor for class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
- SimpleEarlyStoppingStrategy(MLDataSet, int) - Constructor for class org.encog.ml.train.strategy.end.SimpleEarlyStoppingStrategy
-
- SimpleEstimator - Class in org.encog.ml.bayesian.training.estimator
-
A simple probability estimator.
- SimpleEstimator() - Constructor for class org.encog.ml.bayesian.training.estimator.SimpleEstimator
-
- simpleFeedForward(int, int, int, int, boolean) - Static method in class org.encog.util.simple.EncogUtility
-
Create a simple feedforward neural network.
- SimpleIntensityDownsample - Class in org.encog.util.downsample
-
Downsample an image using a simple intensity scale.
- SimpleIntensityDownsample() - Constructor for class org.encog.util.downsample.SimpleIntensityDownsample
-
- SimpleParser - Class in org.encog.util
-
- SimpleParser(String) - Constructor for class org.encog.util.SimpleParser
-
- SimulatedAnnealing<UNIT_TYPE> - Class in org.encog.ml.anneal
-
Simulated annealing is a common training method.
- SimulatedAnnealing() - Constructor for class org.encog.ml.anneal.SimulatedAnnealing
-
- sin(double) - Static method in class org.encog.mathutil.BoundMath
-
Calculate the sin.
- sin() - Method in class org.encog.mathutil.ComplexNumber
-
Sine of this Complex number (doesn't change this Complex number).
- SingleSpeciation - Class in org.encog.ml.ea.species
-
This speciation strategy simply creates a single species that contains the
entire population.
- SingleSpeciation() - Constructor for class org.encog.ml.ea.species.SingleSpeciation
-
- singular(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames
-
Get the singular form for a TimeUnit.
- singular(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames
-
Get the singular form of the specified time unit.
- SingularValueDecomposition - Class in org.encog.mathutil.matrices.decomposition
-
Singular Value Decomposition.
- SingularValueDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition
-
Construct the singular value decomposition
Structure to access U, S and V.
- sinh() - Method in class org.encog.mathutil.ComplexNumber
-
Hyperbolic sine of this Complex number
(doesn't change this Complex number).
- size() - Method in class org.encog.app.analyst.util.CSVHeaders
-
- size() - Method in class org.encog.ca.universe.basic.BasicCellFactory
-
- size() - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- size() - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- size() - Method in interface org.encog.ca.universe.UniverseCell
-
- size() - Method in interface org.encog.ca.universe.UniverseCellFactory
-
- size() - Method in class org.encog.ensemble.data.EnsembleDataSet
-
- size() - Method in class org.encog.mathutil.dimension.MultiDimension
-
- size() - Method in interface org.encog.mathutil.EncogFunction
-
- size() - Method in class org.encog.mathutil.matrices.Matrix
-
Get the size of the array.
- size() - Method in class org.encog.mathutil.probability.vars.VariableList
-
- size() - Method in class org.encog.ml.data.auto.AutoFloatDataSet
-
- size() - Method in class org.encog.ml.data.basic.BasicMLComplexData
- size() - Method in class org.encog.ml.data.basic.BasicMLData
- size() - Method in class org.encog.ml.data.basic.BasicMLDataSet
- size() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
- size() - Method in class org.encog.ml.data.buffer.BufferedMLDataSet
-
- size() - Method in class org.encog.ml.data.folded.FoldedDataSet
-
- size() - Method in interface org.encog.ml.data.MLData
-
- size() - Method in interface org.encog.ml.data.MLDataSet
-
- size() - Method in class org.encog.ml.data.sparse.SparseMLData
- size() - Method in class org.encog.ml.data.specific.BiPolarNeuralData
-
Get the size of this data object.
- size() - Method in class org.encog.ml.data.versatile.MatrixMLDataSet
- size() - Method in interface org.encog.ml.ea.genome.Genome
-
- size() - Method in class org.encog.ml.ea.population.BasicPopulation
- size() - Method in interface org.encog.ml.ea.population.Population
-
- size() - Method in class org.encog.ml.genetic.genome.DoubleArrayGenome
- size() - Method in class org.encog.ml.genetic.genome.IntegerArrayGenome
- size() - Method in class org.encog.ml.graph.BasicPath
-
- size() - Method in class org.encog.ml.graph.search.FrontierHolder
-
- size() - Method in class org.encog.ml.kmeans.BasicCluster
- size() - Method in interface org.encog.ml.MLCluster
-
- size() - Method in class org.encog.ml.prg.EncogProgram
- size() - Method in class org.encog.ml.prg.EncogProgramVariables
-
- size() - Method in class org.encog.ml.prg.extension.FunctionFactory
-
- size() - Method in class org.encog.ml.tree.basic.BasicTreeNode
-
- size() - Method in interface org.encog.ml.tree.TreeNode
-
- size() - Method in class org.encog.neural.freeform.basic.BasicFreeformLayer
- size() - Method in interface org.encog.neural.freeform.FreeformLayer
-
- size() - Method in class org.encog.neural.hyperneat.substrate.SubstrateNode
-
- size() - Method in class org.encog.neural.neat.training.NEATGenome
- SIZE - Static variable in class org.encog.persist.PersistConst
-
- size() - Method in class org.encog.util.datastruct.StackInt
-
- size() - Method in class org.encog.util.datastruct.StackObject
-
- size() - Method in class org.encog.util.datastruct.StackString
-
- size() - Method in class org.encog.util.datastruct.WindowInt
-
- size() - Method in class org.encog.util.kmeans.KMeansUtil
-
- size() - Method in class org.encog.util.obj.ChooseObject
-
- sizeNonBias() - Method in class org.encog.neural.freeform.basic.BasicFreeformLayer
- sizeNonBias() - Method in interface org.encog.neural.freeform.FreeformLayer
-
- skip(long) - Method in class org.encog.parse.PeekableInputStream
-
Skip the specified number of bytes.
- SmartLearningRate - Class in org.encog.neural.networks.training.strategy
-
Attempt to automatically set the learning rate in a learning method that
supports a learning rate.
- SmartLearningRate() - Constructor for class org.encog.neural.networks.training.strategy.SmartLearningRate
-
- SmartMomentum - Class in org.encog.neural.networks.training.strategy
-
Attempt to automatically set a momentum in a training algorithm that supports
momentum.
- SmartMomentum() - Constructor for class org.encog.neural.networks.training.strategy.SmartMomentum
-
- solve(Matrix) - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition
-
Solve A*X = B.
- solve(Matrix) - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
Solve A*X = B
- Solve(double[]) - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
-
- solve(Matrix) - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition
-
Least squares solution of A*X = B
- solve(Matrix) - Method in class org.encog.mathutil.matrices.Matrix
-
Solve A*X = B.
- SOM - Class in org.encog.neural.som
-
A self organizing map neural network.
- SOM() - Constructor for class org.encog.neural.som.SOM
-
Default constructor.
- SOM(int, int) - Constructor for class org.encog.neural.som.SOM
-
The constructor.
- SOMClusterCopyTraining - Class in org.encog.neural.som.training.clustercopy
-
SOM cluster copy is a very simple trainer for SOM's.
- SOMClusterCopyTraining(SOM, MLDataSet) - Constructor for class org.encog.neural.som.training.clustercopy.SOMClusterCopyTraining
-
Construct the object.
- SOMFactory - Class in org.encog.ml.factory.method
-
A factory that is used to produce self-organizing maps.
- SOMFactory() - Constructor for class org.encog.ml.factory.method.SOMFactory
-
- SOMPattern - Class in org.encog.neural.pattern
-
A self organizing map is a neural network pattern with an input and output
layer.
- SOMPattern() - Constructor for class org.encog.neural.pattern.SOMPattern
-
- SortCSV - Class in org.encog.app.analyst.csv.sort
-
Used to sort a CSV file by one, or more, fields.
- SortCSV() - Constructor for class org.encog.app.analyst.csv.sort.SortCSV
-
- SortedField - Class in org.encog.app.analyst.csv.sort
-
Specifies how a field is to be sorted by SortCSV.
- SortedField(int, SortType, boolean) - Constructor for class org.encog.app.analyst.csv.sort.SortedField
-
Construct the object.
- sortGenes() - Method in class org.encog.neural.neat.training.NEATGenome
-
Sort the genes.
- SortGenomesForSpecies - Class in org.encog.ml.ea.sort
-
Sort the gnomes for species.
- SortGenomesForSpecies(EvolutionaryAlgorithm) - Constructor for class org.encog.ml.ea.sort.SortGenomesForSpecies
-
Construct the comparator.
- sortPoints() - Method in class org.encog.ml.data.temporal.TemporalMLDataSet
-
Sort the points.
- SortType - Enum in org.encog.app.analyst.csv.sort
-
The type of sort.
- SourceElement - Class in org.encog.app.analyst.wizard
-
- SourceElement(String, String) - Constructor for class org.encog.app.analyst.wizard.SourceElement
-
- Span - Class in org.encog.bot.browse.range
-
A document range that specifies a span tag, and any embedded tags.
- Span(WebPage) - Constructor for class org.encog.bot.browse.range.Span
-
Construct a span range from the specified web page.
- SparseMLData - Class in org.encog.ml.data.sparse
-
- SparseMLData(double[]) - Constructor for class org.encog.ml.data.sparse.SparseMLData
-
Construct this object with the specified data.
- SparseMLData(double[], int[]) - Constructor for class org.encog.ml.data.sparse.SparseMLData
-
Construct this object with the specified data.
- SparseMLData(int) - Constructor for class org.encog.ml.data.sparse.SparseMLData
-
Construct this object with blank data and a specified size.
- SparseMLData(MLData) - Constructor for class org.encog.ml.data.sparse.SparseMLData
-
Construct a new BasicMLData object from an existing one.
- SPECIAL_CHAR_LIMIT - Static variable in class org.encog.util.http.URLUtility
-
Beyond this number are special chars.
- Speciation - Interface in org.encog.ml.ea.species
-
Defines a speciation strategy.
- Species - Interface in org.encog.ml.ea.species
-
Defines a species.
- SpeciesComparator - Class in org.encog.ml.ea.sort
-
This comparator is used to compare two species.
- SpeciesComparator(EvolutionaryAlgorithm) - Constructor for class org.encog.ml.ea.sort.SpeciesComparator
-
Create a species comparator.
- Splice - Class in org.encog.ml.genetic.crossover
-
A simple cross over where genes are simply "spliced".
- Splice(int) - Constructor for class org.encog.ml.genetic.crossover.Splice
-
Create a slice crossover with the specified cut length.
- SpliceNoRepeat - Class in org.encog.ml.genetic.crossover
-
A simple cross over where genes are simply "spliced".
- SpliceNoRepeat(int) - Constructor for class org.encog.ml.genetic.crossover.SpliceNoRepeat
-
Construct a splice crossover.
- splitColumns(String) - Static method in class org.encog.persist.EncogFileSection
-
Split a delimited string into columns.
- SQLCODEC - Class in org.encog.ml.data.buffer.codec
-
A CODEC that is designed to read data from an SQL source.
- SQLCODEC(Connection, String, int, int) - Constructor for class org.encog.ml.data.buffer.codec.SQLCODEC
-
Create a SQLNeuralDataSet based on the specified connection.
- SQLCODEC(String, int, int, String, String, String, String) - Constructor for class org.encog.ml.data.buffer.codec.SQLCODEC
-
Construct a SQL dataset.
- SQLNeuralDataSet - Class in org.encog.platformspecific.j2se.data
-
A dataset based on a SQL query.
- SQLNeuralDataSet(Connection, String, int, int) - Constructor for class org.encog.platformspecific.j2se.data.SQLNeuralDataSet
-
Create a SQLNeuralDataSet based on the specified connection.
- SQLNeuralDataSet(String, int, int, String, String, String, String) - Constructor for class org.encog.platformspecific.j2se.data.SQLNeuralDataSet
-
Construct a SQL dataset.
- sqrt(double) - Static method in class org.encog.mathutil.BoundMath
-
Calculate the square root.
- sqrt() - Method in class org.encog.mathutil.ComplexNumber
-
Complex square root (doesn't change this complex number).
- square(double) - Static method in class org.encog.mathutil.EncogMath
-
- SRNFactory - Class in org.encog.ml.factory.method
-
A factory that creates simple recurrent neural networks (SRN's), i.e.
- SRNFactory() - Constructor for class org.encog.ml.factory.method.SRNFactory
-
- sse - Variable in class org.encog.mathutil.matrices.hessian.BasicHessian
-
The sum of square error.
- Stacking - Class in org.encog.ensemble.stacking
-
- Stacking(int, int, EnsembleMLMethodFactory, EnsembleTrainFactory, EnsembleAggregator) - Constructor for class org.encog.ensemble.stacking.Stacking
-
- StackInt - Class in org.encog.util.datastruct
-
An integer stack.
- StackInt(int) - Constructor for class org.encog.util.datastruct.StackInt
-
Construct a new stack.
- StackObject<T> - Class in org.encog.util.datastruct
-
- StackObject(int) - Constructor for class org.encog.util.datastruct.StackObject
-
- StackString - Class in org.encog.util.datastruct
-
- StackString(int) - Constructor for class org.encog.util.datastruct.StackString
-
- StandardExtensions - Class in org.encog.ml.prg.extension
-
This class defines the standard opcodes for Encog programs.
- StandardExtensions() - Constructor for class org.encog.ml.prg.extension.StandardExtensions
-
- start() - Method in class org.encog.ca.runner.BasicCARunner
-
- start() - Method in interface org.encog.ca.runner.CARunner
-
- start() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
-
Start the manager.
- start() - Method in class org.encog.util.Stopwatch
-
Start the stop watch.
- START_MOMENTUM - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum
-
The starting momentum.
- startConsoleLogging() - Method in class org.encog.plugin.system.SystemLoggingPlugin
-
Start logging to the console.
- startElement(String, String, String, Attributes) - Method in class org.encog.ml.bayesian.bif.BIFHandler
- startNewSequence() - Method in class org.encog.ml.data.basic.BasicMLSequenceSet
-
- startNewSequence() - Method in interface org.encog.ml.data.MLSequenceSet
-
Cause a "break" in the data by creating a the beginning of a new sequence.
- startNode - Variable in class org.encog.ml.schedule.ScheduleGraph
-
- State - Interface in org.encog.ml.world
-
- StateDistribution - Interface in org.encog.ml.hmm.distributions
-
This class represents a "state distribution".
- stateSequence() - Method in class org.encog.ml.hmm.alog.ViterbiCalculator
-
- StatusReportable - Interface in org.encog
-
This class allows for Encog jobs to report their current status, as they run.
- stimulateNeuron(double, int, int) - Method in class org.encog.neural.prune.PruneSelective
-
Stimulate the specified neuron by the specified percent.
- stimulateWeakNeurons(int, int, double) - Method in class org.encog.neural.prune.PruneSelective
-
Stimulate weaker neurons on a layer.
- stop() - Method in class org.encog.ca.runner.BasicCARunner
-
- stop() - Method in interface org.encog.ca.runner.CARunner
-
- stop() - Method in class org.encog.util.concurrency.job.ConcurrentJob
-
Request the process to stop.
- stop() - Method in class org.encog.util.Stopwatch
-
Stop the stopwatch.
- stopCurrentTask() - Method in class org.encog.app.analyst.EncogAnalyst
-
Stop the current task.
- stopLogging() - Method in class org.encog.plugin.system.SystemLoggingPlugin
-
Stop any console or file logging.
- StopTrainingStrategy - Class in org.encog.ml.train.strategy
-
This strategy will indicate once training is no longer improving the neural
network by a specified amount, over a specified number of cycles.
- StopTrainingStrategy() - Constructor for class org.encog.ml.train.strategy.StopTrainingStrategy
-
Construct the strategy with default options.
- StopTrainingStrategy(double, int) - Constructor for class org.encog.ml.train.strategy.StopTrainingStrategy
-
Construct the strategy with the specified parameters.
- Stopwatch - Class in org.encog.util
-
A stopwatch, meant to emulate the C# Stopwatch class.
- Stopwatch() - Constructor for class org.encog.util.Stopwatch
-
Construct a stopwatch.
- storeColumn(String, double) - Method in class org.encog.app.quant.ninja.NinjaStreamWriter
-
Store a column.
- Strategy - Interface in org.encog.ml.train.strategy
-
Training strategies can be added to training algorithms.
- string2AnalystFileFormat(String) - Static method in class org.encog.app.analyst.util.ConvertStringConst
-
Convert a string to an analyst file format.
- string2double(String) - Static method in class org.encog.mathutil.Convert
-
Convert a string to a double.
- string2int(String) - Static method in class org.encog.mathutil.Convert
-
Convert a string to an int.
- stringToKernel(String) - Static method in class org.encog.neural.pnn.PersistBasicPNN
-
Convert a string to a PNN kernel.
- stringToNeuronType(String) - Static method in class org.encog.neural.neat.PersistNEATPopulation
-
- stringToOutputMode(String) - Static method in class org.encog.neural.pnn.PersistBasicPNN
-
Convert a string to a PNN output mode.
- stripTags(String) - Static method in class org.encog.bot.BotUtil
-
Strip any HTML or XML tags from the specified string.
- stripTime(Date) - Static method in class org.encog.util.time.NumericDateUtil
-
- sub(double[], double[]) - Method in class org.encog.mathutil.VectorAlgebra
-
v1 = v1 - v2
- sub(ExpressionValue, ExpressionValue) - Static method in class org.encog.ml.prg.expvalue.EvaluateExpr
-
Perform a subtract on two expression values.
- sub() - Method in class org.encog.util.datastruct.StackInt
-
- Substrate - Class in org.encog.neural.hyperneat.substrate
-
The substrate defines the structure of the produced HyperNEAT network.
- Substrate(int) - Constructor for class org.encog.neural.hyperneat.substrate.Substrate
-
Construct a substrate with the specified number of dimensions in the
input/output layers.
- SubstrateFactory - Class in org.encog.neural.hyperneat.substrate
-
Produce substrates for various topologies.
- SubstrateFactory() - Constructor for class org.encog.neural.hyperneat.substrate.SubstrateFactory
-
- SubstrateLink - Class in org.encog.neural.hyperneat.substrate
-
A substrate link.
- SubstrateLink(SubstrateNode, SubstrateNode) - Constructor for class org.encog.neural.hyperneat.substrate.SubstrateLink
-
- SubstrateNode - Class in org.encog.neural.hyperneat.substrate
-
A substrate node.
- SubstrateNode(int, int) - Constructor for class org.encog.neural.hyperneat.substrate.SubstrateNode
-
Construct this node.
- subtract(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Return the results of subtracting one matrix from another.
- subtract(double[], double[]) - Static method in class org.encog.util.EngineArray
-
- SubtreeCrossover - Class in org.encog.ml.prg.opp
-
Perform a type-safe subtree crossover.
- SubtreeCrossover() - Constructor for class org.encog.ml.prg.opp.SubtreeCrossover
-
- SubtreeMutation - Class in org.encog.ml.prg.opp
-
Perform a type-safe subtree mutation.
- SubtreeMutation(EncogProgramContext, int) - Constructor for class org.encog.ml.prg.opp.SubtreeMutation
-
Construct the subtree mutation object.
- SuccessorState - Class in org.encog.ml.world
-
- SuccessorState(State, double) - Constructor for class org.encog.ml.world.SuccessorState
-
- suggestModelArchitecture(VersatileMLDataSet) - Method in class org.encog.ml.model.config.FeedforwardConfig
-
Suggest a model architecture, based on a dataset.
- suggestModelArchitecture(VersatileMLDataSet) - Method in interface org.encog.ml.model.config.MethodConfig
-
Suggest a model architecture, based on a dataset.
- suggestModelArchitecture(VersatileMLDataSet) - Method in class org.encog.ml.model.config.NEATConfig
-
Suggest a model architecture, based on a dataset.
- suggestModelArchitecture(VersatileMLDataSet) - Method in class org.encog.ml.model.config.PNNConfig
-
Suggest a model architecture, based on a dataset.
- suggestModelArchitecture(VersatileMLDataSet) - Method in class org.encog.ml.model.config.RBFNetworkConfig
-
Suggest a model architecture, based on a dataset.
- suggestModelArchitecture(VersatileMLDataSet) - Method in class org.encog.ml.model.config.SVMConfig
-
Suggest a model architecture, based on a dataset.
- suggestNormalizationStrategy(VersatileMLDataSet, String) - Method in class org.encog.ml.model.config.FeedforwardConfig
-
Suggest a normalization strategy based on a dataset.
- suggestNormalizationStrategy(VersatileMLDataSet, String) - Method in interface org.encog.ml.model.config.MethodConfig
-
Suggest a normalization strategy based on a dataset.
- suggestNormalizationStrategy(VersatileMLDataSet, String) - Method in class org.encog.ml.model.config.NEATConfig
-
Suggest a normalization strategy based on a dataset.
- suggestNormalizationStrategy(VersatileMLDataSet, String) - Method in class org.encog.ml.model.config.PNNConfig
-
Suggest a normalization strategy based on a dataset.
- suggestNormalizationStrategy(VersatileMLDataSet, String) - Method in class org.encog.ml.model.config.RBFNetworkConfig
-
Suggest a normalization strategy based on a dataset.
- suggestNormalizationStrategy(VersatileMLDataSet, String) - Method in class org.encog.ml.model.config.SVMConfig
-
Suggest a normalization strategy based on a dataset.
- suggestTrainingArgs(String) - Method in class org.encog.ml.model.config.FeedforwardConfig
-
Suggest training arguments.
- suggestTrainingArgs(String) - Method in interface org.encog.ml.model.config.MethodConfig
-
Suggest training arguments.
- suggestTrainingArgs(String) - Method in class org.encog.ml.model.config.NEATConfig
-
Suggest training arguments.
- suggestTrainingArgs(String) - Method in class org.encog.ml.model.config.PNNConfig
-
Suggest training arguments.
- suggestTrainingArgs(String) - Method in class org.encog.ml.model.config.RBFNetworkConfig
-
Suggest training arguments.
- suggestTrainingArgs(String) - Method in class org.encog.ml.model.config.SVMConfig
-
- suggestTrainingType() - Method in class org.encog.ml.model.config.FeedforwardConfig
-
Suggest a training type.
- suggestTrainingType() - Method in interface org.encog.ml.model.config.MethodConfig
-
Suggest a training type.
- suggestTrainingType() - Method in class org.encog.ml.model.config.NEATConfig
-
Suggest a training type.
- suggestTrainingType() - Method in class org.encog.ml.model.config.PNNConfig
-
Suggest a training type.
- suggestTrainingType() - Method in class org.encog.ml.model.config.RBFNetworkConfig
-
Suggest a training type.
- suggestTrainingType() - Method in class org.encog.ml.model.config.SVMConfig
-
Suggest a training type.
- sum() - Method in class org.encog.mathutil.matrices.Matrix
-
Sum all of the values in the matrix.
- SUMS - Static variable in class org.encog.persist.PersistConst
-
Sums
- suspendEncoding() - Method in class org.encog.util.text.Base64.OutputStream
-
Suspends encoding of the stream.
- SV - Variable in class org.encog.mathutil.libsvm.svm_model
-
- sv_coef - Variable in class org.encog.mathutil.libsvm.svm_model
-
- SVD - Class in org.encog.neural.rbf.training
-
Perform a SVD decomp on a matrix.
- SVD() - Constructor for class org.encog.neural.rbf.training.SVD
-
- svdbksb(double[][], double[], double[][], double[][], double[][]) - Static method in class org.encog.neural.rbf.training.SVD
-
- svdcmp(double[][], double[], double[][]) - Static method in class org.encog.neural.rbf.training.SVD
-
- svdfit(double[][], double[][], double[][], RadialBasisFunction[]) - Static method in class org.encog.neural.rbf.training.SVD
-
- SVDTraining - Class in org.encog.neural.rbf.training
-
Train a RBF neural network using a SVD.
- SVDTraining(RBFNetwork, MLDataSet) - Constructor for class org.encog.neural.rbf.training.SVDTraining
-
Construct the training object.
- svm - Class in org.encog.mathutil.libsvm
-
- svm() - Constructor for class org.encog.mathutil.libsvm.svm
-
- SVM - Class in org.encog.ml.svm
-
This is a network that is backed by one or more Support Vector Machines
(SVM).
- SVM() - Constructor for class org.encog.ml.svm.SVM
-
Construct the SVM.
- SVM(int, boolean) - Constructor for class org.encog.ml.svm.SVM
-
Construct an SVM network.
- SVM(int, SVMType, KernelType) - Constructor for class org.encog.ml.svm.SVM
-
Construct a SVM network.
- SVM(svm_model) - Constructor for class org.encog.ml.svm.SVM
-
Construct a SVM from a model.
- svm_check_parameter(svm_problem, svm_parameter) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_check_probability_model(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_cross_validation(svm_problem, svm_parameter, int, double[]) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_get_labels(svm_model, int[]) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_get_nr_class(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_get_svm_type(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_get_svr_probability(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_load_model(String) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_load_model(BufferedReader) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_model - Class in org.encog.mathutil.libsvm
-
This class was taken from the libsvm package.
- svm_model() - Constructor for class org.encog.mathutil.libsvm.svm_model
-
- svm_node - Class in org.encog.mathutil.libsvm
-
This class was taken from the libsvm package.
- svm_node() - Constructor for class org.encog.mathutil.libsvm.svm_node
-
- svm_parameter - Class in org.encog.mathutil.libsvm
-
This class was taken from the libsvm package.
- svm_parameter() - Constructor for class org.encog.mathutil.libsvm.svm_parameter
-
- svm_predict(svm_model, svm_node[]) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_predict_probability(svm_model, svm_node[], double[]) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_predict_values(svm_model, svm_node[], double[]) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_print_interface - Interface in org.encog.mathutil.libsvm
-
This class was taken from the libsvm package.
- svm_problem - Class in org.encog.mathutil.libsvm
-
This class was taken from the libsvm package.
- svm_problem() - Constructor for class org.encog.mathutil.libsvm.svm_problem
-
- svm_save_model(String, svm_model) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_save_model(DataOutputStream, svm_model) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_set_print_string_function(svm_print_interface) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_train(svm_problem, svm_parameter) - Static method in class org.encog.mathutil.libsvm.svm
-
- svm_type - Variable in class org.encog.mathutil.libsvm.svm_parameter
-
- SVMConfig - Class in org.encog.ml.model.config
-
Config class for EncogModel to use an SVM.
- SVMConfig() - Constructor for class org.encog.ml.model.config.SVMConfig
-
- SVMFactory - Class in org.encog.ml.factory.method
-
A factory that is used to create support vector machines (SVM).
- SVMFactory() - Constructor for class org.encog.ml.factory.method.SVMFactory
-
- SVMFactory - Class in org.encog.ml.factory.train
-
A factory to create SVM trainers.
- SVMFactory() - Constructor for class org.encog.ml.factory.train.SVMFactory
-
- SVMPattern - Class in org.encog.neural.pattern
-
A pattern to create support vector machines.
- SVMPattern() - Constructor for class org.encog.neural.pattern.SVMPattern
-
- SVMSearchFactory - Class in org.encog.ml.factory.train
-
A factory that creates SVM-search trainers.
- SVMSearchFactory() - Constructor for class org.encog.ml.factory.train.SVMSearchFactory
-
- SVMSearchTrain - Class in org.encog.ml.svm.training
-
Provides training for Support Vector Machine networks.
- SVMSearchTrain(SVM, MLDataSet) - Constructor for class org.encog.ml.svm.training.SVMSearchTrain
-
Construct a trainer for an SVM network.
- SVMTrain - Class in org.encog.ml.svm.training
-
Provides training for Support Vector Machine networks.
- SVMTrain(SVM, MLDataSet) - Constructor for class org.encog.ml.svm.training.SVMTrain
-
Construct a trainer for an SVM network.
- SVMType - Enum in org.encog.ml.svm
-
Supports both class and new support vector calculations, as well as one-class
distribution.
- swap(int, int) - Method in interface org.encog.ml.genetic.genome.ArrayGenome
-
Swap two elements in this genome.
- swap(int, int) - Method in class org.encog.ml.genetic.genome.DoubleArrayGenome
-
Swap two elements in this genome.
- swap(int, int) - Method in class org.encog.ml.genetic.genome.IntegerArrayGenome
-
Swap two elements in this genome.
- SystemActivationPlugin - Class in org.encog.plugin.system
-
- SystemActivationPlugin() - Constructor for class org.encog.plugin.system.SystemActivationPlugin
-
- SystemLoggingPlugin - Class in org.encog.plugin.system
-
This is the built-in logging plugin for Encog.
- SystemLoggingPlugin() - Constructor for class org.encog.plugin.system.SystemLoggingPlugin
-
- SystemMethodsPlugin - Class in org.encog.plugin.system
-
The system machine learning methods plugin.
- SystemMethodsPlugin() - Constructor for class org.encog.plugin.system.SystemMethodsPlugin
-
- SystemTrainingPlugin - Class in org.encog.plugin.system
-
- SystemTrainingPlugin() - Constructor for class org.encog.plugin.system.SystemTrainingPlugin
-
- TableLine - Class in org.encog.ml.bayesian.table
-
A line from a Bayesian truth table.
- TableLine(double, int, int[]) - Constructor for class org.encog.ml.bayesian.table.TableLine
-
Construct a truth table line.
- tablePair(String, String) - Method in class org.encog.util.HTMLReport
-
- Tag - Class in org.encog.parse.tags
-
HTMLTag: This class holds a single HTML tag.
- Tag() - Constructor for class org.encog.parse.tags.Tag
-
- Tag.Type - Enum in org.encog.parse.tags
-
Tag types.
- TAG_BEGIN_TRAINING - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for begin training.
- TAG_BIAS_ACTIVATION - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for bias activation.
- TAG_CONNECTION_LIMIT - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for connection limit.
- TAG_CONTEXT_TARGET_OFFSET - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for context target offset.
- TAG_CONTEXT_TARGET_SIZE - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for context target size.
- TAG_COVARIANCE - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_DIST_TYPE - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_END_TRAINING - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for end training.
- TAG_HAS_CONTEXT - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for has context.
- TAG_INSTAR - Static variable in class org.encog.neural.pattern.CPNPattern
-
The tag for the INSTAR layer.
- TAG_ITEMS - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_LAYER_CONTEXT_COUNT - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for layer context count.
- TAG_LAYER_COUNTS - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for layer counts.
- TAG_LAYER_FEED_COUNTS - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for layer feed counts.
- TAG_LAYER_INDEX - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for layer index.
- TAG_LIMIT - Static variable in class org.encog.neural.networks.BasicNetwork
-
Tag used for the connection limit.
- TAG_MEAN - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_OUTSTAR - Static variable in class org.encog.neural.pattern.CPNPattern
-
The tag for the OUTSTAR layer.
- TAG_PI - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_PROBABILITIES - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_STATES - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_TRANSITION - Static variable in class org.encog.ml.hmm.HiddenMarkovModel
-
- TAG_WEIGHT_INDEX - Static variable in class org.encog.neural.networks.BasicNetwork
-
The property for weight index.
- tagColumn(String, int, int, boolean) - Static method in class org.encog.app.analyst.util.CSVHeaders
-
Tag a column with part # and timeslice.
- TagConst - Class in org.encog.parse.tags
-
Constants to use while parsing the tags.
- TagDataUnit - Class in org.encog.bot.dataunit
-
A data unit that holds a tag.
- TagDataUnit() - Constructor for class org.encog.bot.dataunit.TagDataUnit
-
- tan() - Method in class org.encog.mathutil.ComplexNumber
-
Tangent of this Complex number (doesn't change this Complex number).
- tanh(double) - Static method in class org.encog.mathutil.BoundMath
-
Calculate TANH, within bounds.
- TargetLanguage - Enum in org.encog.app.generate
-
Specifies the target language for Encog code generation.
- task(TreeNode) - Method in class org.encog.ml.tree.traverse.tasks.TaskCountNodes
- task(TreeNode) - Method in class org.encog.ml.tree.traverse.tasks.TaskGetNodeIndex
- task(TreeNode) - Method in class org.encog.ml.tree.traverse.tasks.TaskReplaceNode
- task(TreeNode) - Method in interface org.encog.ml.tree.traverse.TreeTraversalTask
-
- task(FreeformConnection) - Method in interface org.encog.neural.freeform.task.ConnectionTask
-
The task.
- task(FreeformNeuron) - Method in interface org.encog.neural.freeform.task.NeuronTask
-
The task.
- TASK_FULL - Static variable in class org.encog.app.analyst.EncogAnalyst
-
The name of the task that SHOULD everything.
- TaskCountNodes - Class in org.encog.ml.tree.traverse.tasks
-
Count the nodes in an acyclic tree.
- TaskCountNodes() - Constructor for class org.encog.ml.tree.traverse.tasks.TaskCountNodes
-
Construct the task.
- TaskGetNodeIndex - Class in org.encog.ml.tree.traverse.tasks
-
Get a node by index.
- TaskGetNodeIndex(int) - Constructor for class org.encog.ml.tree.traverse.tasks.TaskGetNodeIndex
-
- TaskGroup - Class in org.encog.util.concurrency
-
A task group is a group of tasks that you would like to execute at once.
- TaskGroup(int) - Constructor for class org.encog.util.concurrency.TaskGroup
-
Create a task group with the specified id.
- TaskReplaceNode - Class in org.encog.ml.tree.traverse.tasks
-
Task to replace a node.
- TaskReplaceNode(TreeNode, TreeNode) - Constructor for class org.encog.ml.tree.traverse.tasks.TaskReplaceNode
-
- taskStarting() - Method in class org.encog.util.concurrency.TaskGroup
-
Notify that a task is starting.
- taskStopping() - Method in class org.encog.util.concurrency.TaskGroup
-
Notify that a task is stopping.
- TEMP_GRADIENT - Static variable in class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Temp value #0: the gradient.
- TEMP_LAST_GRADIENT - Static variable in class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Temp value #1: the last gradient.
- TEMP_LAST_WEIGHT_DELTA - Static variable in class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Temp value #3: the the last weight delta.
- TEMP_UPDATE - Static variable in class org.encog.neural.freeform.training.FreeformResilientPropagation
-
Temp value #2: the update.
- TEMPERATURE - Static variable in class org.encog.persist.PersistConst
-
Temperature.
- TemplateGenerator - Interface in org.encog.app.generate.generators
-
This interface defines a generator that works by template.
- TemporalDataDescription - Class in org.encog.ml.data.temporal
-
This class describes one unit of input, or output, to a temporal neural
network.
- TemporalDataDescription(ActivationFunction, double, double, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.ml.data.temporal.TemporalDataDescription
-
Construct a data description item.
- TemporalDataDescription(ActivationFunction, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.ml.data.temporal.TemporalDataDescription
-
Construct a data description with an activation function, but no range.
- TemporalDataDescription(TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.ml.data.temporal.TemporalDataDescription
-
Construct a data description with no activation function or range.
- TemporalDataDescription.Type - Enum in org.encog.ml.data.temporal
-
The type of data requested.
- TemporalError - Exception in org.encog.ml.data.temporal
-
Error occurred processing temporal data.
- TemporalError(String) - Constructor for exception org.encog.ml.data.temporal.TemporalError
-
Construct a message exception.
- TemporalError(Throwable) - Constructor for exception org.encog.ml.data.temporal.TemporalError
-
Construct an exception that holds another exception.
- TemporalMLDataSet - Class in org.encog.ml.data.temporal
-
This class implements a temporal neural data set.
- TemporalMLDataSet(int, int) - Constructor for class org.encog.ml.data.temporal.TemporalMLDataSet
-
Construct a dataset.
- TemporalPoint - Class in org.encog.ml.data.temporal
-
A temporal point is all of the data captured at one point in time to be used
for prediction.
- TemporalPoint(int) - Constructor for class org.encog.ml.data.temporal.TemporalPoint
-
Construct a temporal point of the specified size.
- TemporalType - Enum in org.encog.util.arrayutil
-
Operations that the temporal class may perform on fields.
- TemporalWindowArray - Class in org.encog.util.arrayutil
-
Produce a time-series from an array.
- TemporalWindowArray(int, int) - Constructor for class org.encog.util.arrayutil.TemporalWindowArray
-
Construct a time-series from an array.
- TemporalWindowField - Class in org.encog.util.arrayutil
-
This class specifies how fields are to be used by the TemporalWindowCSV
class.
- TemporalWindowField(String) - Constructor for class org.encog.util.arrayutil.TemporalWindowField
-
Construct the object.
- tempTrainingAllocate(int, int) - Method in class org.encog.neural.freeform.FreeformNetwork
-
Allocate temp training space.
- tempTrainingClear() - Method in class org.encog.neural.freeform.FreeformNetwork
-
Clear the temp training data.
- TempTrainingData - Interface in org.encog.neural.freeform
-
Some training methods require that temp data be stored during the training
process.
- Test - Class in org.encog
-
- Test() - Constructor for class org.encog.Test
-
- TextDataUnit - Class in org.encog.bot.dataunit
-
A data unit that holds text.
- TextDataUnit() - Constructor for class org.encog.bot.dataunit.TextDataUnit
-
- ThermalNetwork - Class in org.encog.neural.thermal
-
The thermal network forms the base class for Hopfield and Boltzmann machines.
- ThermalNetwork() - Constructor for class org.encog.neural.thermal.ThermalNetwork
-
Default constructor.
- ThermalNetwork(int) - Constructor for class org.encog.neural.thermal.ThermalNetwork
-
Construct the network with the specicified neuron count.
- thirds(double) - Static method in class org.encog.mathutil.EncogMath
-
Transform a number in the range (-1,1) to a tri-state value indicated by
-1, 0 or 1.
- THRESHOLDS - Static variable in class org.encog.persist.PersistConst
-
Thresholds.
- ThresholdSpeciation - Class in org.encog.ml.ea.species
-
Speciate based on threshold.
- ThresholdSpeciation() - Constructor for class org.encog.ml.ea.species.ThresholdSpeciation
-
- tick() - Method in class org.encog.ml.world.basic.BasicAgent
-
- tick() - Method in class org.encog.ml.world.basic.BasicWorld
-
- tick() - Method in interface org.encog.ml.world.World
-
- tick() - Method in interface org.encog.ml.world.WorldAgent
-
- TickerSymbol - Class in org.encog.ml.data.market
-
Holds a ticker symbol and exchange.
- TickerSymbol(String) - Constructor for class org.encog.ml.data.market.TickerSymbol
-
Construct a ticker symbol with no exchange.
- TickerSymbol(String, String) - Constructor for class org.encog.ml.data.market.TickerSymbol
-
Construct a ticker symbol with exchange.
- TIME - Static variable in class org.encog.app.analyst.csv.basic.FileData
-
The time.
- time2Int(Date) - Static method in class org.encog.util.time.NumericDateUtil
-
- times(ComplexNumber) - Method in class org.encog.mathutil.ComplexNumber
-
Complex multiplication (doesn't change this Complex number).
- times(double) - Method in class org.encog.ml.data.basic.BasicMLData
-
Multiply one data element with another.
- TimeSeriesUtil - Class in org.encog.app.analyst.csv
-
A utility used to breat data into time-series lead and lag.
- TimeSeriesUtil(EncogAnalyst, boolean, List<String>) - Constructor for class org.encog.app.analyst.csv.TimeSeriesUtil
-
Construct the time-series utility.
- TimeSpan - Class in org.encog.util.time
-
A timespan between two Dates.
- TimeSpan(Date, Date) - Constructor for class org.encog.util.time.TimeSpan
-
Construct a time span.
- TimeUnit - Enum in org.encog.util.time
-
Time units.
- TimeUnitNames - Interface in org.encog.util.time
-
Get the name or code for a time unit.
- title(String) - Method in class org.encog.util.HTMLReport
-
- toBinary(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert bipolar to binary.
- toBiPolar(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert binary to bipolar.
- toBooleanValue() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- toBrokenList(StringBuilder, double[]) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Create an array list broken into 10 columns.
- toBrokenList(StringBuilder, int[]) - Method in class org.encog.app.generate.generators.AbstractTemplateGenerator
-
Create an array list broken into 10 columns.
- toDots(String) - Static method in class org.encog.app.analyst.script.prop.ScriptProperties
-
Convert a key to the dot form.
- toFloatValue() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- toFullString() - Method in class org.encog.ml.bayesian.BayesianChoice
-
- toFullString() - Method in class org.encog.ml.bayesian.BayesianEvent
-
- toIntValue() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- toList(MLDataSet) - Static method in class org.encog.ml.data.basic.BasicMLDataSet
-
Concert the data set to a list.
- toList(CSVFormat, StringBuilder, double[]) - Static method in class org.encog.util.csv.NumberList
-
Convert an array of doubles to a comma separated list.
- toList(CSVFormat, int, StringBuilder, double[]) - Static method in class org.encog.util.csv.NumberList
-
- toListInt(CSVFormat, StringBuilder, int[]) - Static method in class org.encog.util.csv.NumberList
-
- toNormalizedBinary(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
-
Convert to binary and normalize.
- TOO_BIG - Static variable in class org.encog.mathutil.BoundNumbers
-
Too big of a number.
- TOO_SMALL - Static variable in class org.encog.mathutil.BoundNumbers
-
Too small of a number.
- toPackedArray() - Method in class org.encog.mathutil.matrices.Matrix
-
Convert the matrix into a packed array.
- toSimpleString(EventState) - Static method in class org.encog.ml.bayesian.query.sample.EventState
-
Convert a state to a simple string.
- toString() - Method in class org.encog.app.analyst.analyze.AnalyzedField
- toString() - Method in class org.encog.app.analyst.analyze.PerformAnalysis
- toString() - Method in class org.encog.app.analyst.commands.Cmd
- toString() - Method in class org.encog.app.analyst.csv.basic.BasicFile
- toString() - Method in class org.encog.app.analyst.csv.filter.ExcludedField
- toString() - Method in class org.encog.app.analyst.csv.segregate.SegregateTargetPercent
- toString() - Method in class org.encog.app.analyst.csv.sort.SortedField
- toString() - Method in class org.encog.app.analyst.script.AnalystClassItem
- toString() - Method in class org.encog.app.analyst.script.normalize.AnalystField
- toString() - Method in class org.encog.app.analyst.script.normalize.AnalystNormalize
- toString() - Method in class org.encog.app.analyst.script.prop.PropertyEntry
- toString() - Method in class org.encog.app.analyst.script.prop.ScriptProperties
- toString() - Method in class org.encog.app.analyst.script.segregate.AnalystSegregateTarget
- toString() - Method in class org.encog.app.analyst.script.task.AnalystTask
- toString() - Method in class org.encog.bot.browse.Address
- toString() - Method in class org.encog.bot.browse.Browser
- toString() - Method in class org.encog.bot.browse.range.Div
- toString() - Method in class org.encog.bot.browse.range.Form
- toString() - Method in class org.encog.bot.browse.range.FormElement
- toString() - Method in class org.encog.bot.browse.range.Link
- toString() - Method in class org.encog.bot.browse.range.Span
- toString() - Method in class org.encog.bot.browse.WebPage
- toString() - Method in class org.encog.bot.dataunit.CodeDataUnit
- toString() - Method in class org.encog.bot.dataunit.TagDataUnit
- toString() - Method in class org.encog.bot.dataunit.TextDataUnit
- toString() - Method in class org.encog.bot.rss.RSS
- toString() - Method in class org.encog.bot.rss.RSSItem
- toString() - Method in class org.encog.ca.program.generic.Trans
-
- toString() - Method in class org.encog.ca.runner.BasicCARunner
-
- toString() - Method in class org.encog.ca.universe.basic.BasicContinuousCell
-
- toString() - Method in class org.encog.ca.universe.basic.BasicDiscreteCell
-
- toString() - Method in class org.encog.mathutil.ComplexNumber
-
String representation of this Complex number.
- toString() - Method in class org.encog.mathutil.dimension.MultiDimension
-
- toString() - Method in class org.encog.mathutil.IntPair
-
- toString() - Method in class org.encog.mathutil.matrices.Matrix
- toString() - Method in class org.encog.mathutil.NumericRange
- toString() - Method in class org.encog.mathutil.probability.vars.RandomVariable
-
- toString() - Method in class org.encog.mathutil.rbf.BasicRBF
-
- toString() - Method in class org.encog.ml.bayesian.BayesianChoice
- toString() - Method in class org.encog.ml.bayesian.BayesianEvent
- toString() - Method in class org.encog.ml.bayesian.BayesianNetwork
- toString() - Method in class org.encog.ml.bayesian.parse.ParsedChoice
- toString() - Method in class org.encog.ml.bayesian.parse.ParsedEvent
- toString() - Method in class org.encog.ml.bayesian.parse.ParsedProbability
- toString() - Method in class org.encog.ml.bayesian.query.enumerate.EnumerationQuery
- toString() - Method in class org.encog.ml.bayesian.query.sample.EventState
- toString() - Method in class org.encog.ml.bayesian.query.sample.SamplingQuery
- toString() - Method in class org.encog.ml.bayesian.table.BayesianTable
- toString() - Method in class org.encog.ml.bayesian.table.TableLine
- toString() - Method in class org.encog.ml.data.auto.AutoFloatColumn
-
- toString() - Method in class org.encog.ml.data.basic.BasicMLComplexData
- toString() - Method in class org.encog.ml.data.basic.BasicMLData
- toString() - Method in class org.encog.ml.data.basic.BasicMLDataPair
- toString() - Method in class org.encog.ml.data.sparse.SparseMLData
- toString() - Method in class org.encog.ml.data.specific.BiPolarNeuralData
- toString() - Method in class org.encog.ml.data.temporal.TemporalPoint
- toString() - Method in class org.encog.ml.data.versatile.columns.ColumnDefinition
- toString() - Method in class org.encog.ml.data.versatile.NormalizationHelper
- toString() - Method in class org.encog.ml.ea.genome.BasicGenome
- toString() - Method in class org.encog.ml.ea.species.BasicSpecies
- toString() - Method in class org.encog.ml.graph.BasicEdge
-
- toString() - Method in class org.encog.ml.graph.BasicNode
-
- toString() - Method in class org.encog.ml.graph.BasicPath
-
- toString() - Method in class org.encog.ml.prg.EncogProgram
- toString() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
- toString() - Method in class org.encog.ml.prg.extension.BasicTemplate
- toString() - Method in class org.encog.ml.prg.ProgramNode
- toString() - Method in class org.encog.ml.prg.VariableMapping
- toString() - Method in class org.encog.ml.schedule.ActionNode
-
- toString() - Method in class org.encog.ml.world.basic.BasicAction
-
- toString() - Method in class org.encog.ml.world.basic.BasicAgent
-
- toString() - Method in class org.encog.ml.world.basic.BasicState
-
- toString() - Method in class org.encog.ml.world.grid.GridState
-
- toString() - Method in class org.encog.ml.world.SuccessorState
-
- toString() - Method in class org.encog.neural.flat.FlatLayer
- toString() - Method in class org.encog.neural.freeform.basic.BasicFreeformConnection
- toString() - Method in class org.encog.neural.freeform.basic.BasicFreeformNeuron
- toString() - Method in class org.encog.neural.freeform.FreeformContextNeuron
- toString() - Method in class org.encog.neural.hyperneat.substrate.SubstrateLink
- toString() - Method in class org.encog.neural.hyperneat.substrate.SubstrateNode
- toString() - Method in class org.encog.neural.neat.NEATLink
- toString() - Method in class org.encog.neural.neat.training.NEATGenome
-
- toString() - Method in class org.encog.neural.neat.training.NEATInnovation
- toString() - Method in class org.encog.neural.neat.training.NEATLinkGene
- toString() - Method in class org.encog.neural.neat.training.NEATNeuronGene
- toString() - Method in class org.encog.neural.neat.training.opp.links.MutatePerturbLinkWeight
- toString() - Method in class org.encog.neural.neat.training.opp.links.MutateResetLinkWeight
- toString() - Method in class org.encog.neural.neat.training.opp.links.SelectFixed
- toString() - Method in class org.encog.neural.neat.training.opp.links.SelectProportion
- toString() - Method in class org.encog.neural.neat.training.opp.NEATMutateWeights
- toString() - Method in class org.encog.neural.networks.BasicNetwork
- toString() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
- toString() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
- toString() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
- toString() - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
- toString() - Method in class org.encog.parse.tags.read.ReadTags
- toString() - Method in class org.encog.parse.tags.Tag
-
Convert this tag back into string form, with the beginning < and ending
>.
- toString() - Method in class org.encog.persist.EncogFileSection
- toString() - Method in class org.encog.util.arrayutil.ClassItem
- toString() - Method in class org.encog.util.arrayutil.NormalizedField
- toString() - Method in class org.encog.util.arrayutil.TemporalWindowField
- toString() - Method in class org.encog.util.datastruct.StackInt
-
- toString() - Method in class org.encog.util.datastruct.StackObject
-
- toString() - Method in class org.encog.util.datastruct.StackString
-
- toString() - Method in class org.encog.util.HTMLReport
-
- toString() - Method in class org.encog.util.normalize.input.InputFieldEncogCollection
- toString() - Method in class org.encog.util.normalize.output.OutputFieldDirect
- toString() - Method in class org.encog.util.SimpleParser
-
- toString() - Method in class org.encog.util.text.BagOfWords
-
- toStringLiteral(File) - Static method in class org.encog.util.file.FileUtil
-
- toStringValue() - Method in class org.encog.ml.prg.expvalue.ExpressionValue
-
- TOTAL_PCT - Static variable in class org.encog.app.analyst.csv.segregate.SegregateCSV
-
TOtal percents should add to this.
- TournamentSelection - Class in org.encog.ml.ea.opp.selection
-
Tournament select can be used to select a fit (or unfit) genome from a
species.
- TournamentSelection(EvolutionaryAlgorithm, int) - Constructor for class org.encog.ml.ea.opp.selection.TournamentSelection
-
Construct a tournament selection.
- train(double, double, EnsembleDataSet, boolean) - Method in class org.encog.ensemble.adaboost.AdaBoost
-
- train() - Method in class org.encog.ensemble.aggregator.Averaging
-
- train() - Method in class org.encog.ensemble.aggregator.MajorityVoting
-
- train() - Method in class org.encog.ensemble.aggregator.MetaClassifier
-
- train(double, double, EnsembleDataSet, boolean) - Method in class org.encog.ensemble.Ensemble
-
Train the ensemble to a target accuracy
- train(double, double, EnsembleDataSet) - Method in class org.encog.ensemble.Ensemble
-
Train the ensemble to a target accuracy
- train() - Method in interface org.encog.ensemble.EnsembleAggregator
-
- train(double) - Method in interface org.encog.ensemble.EnsembleML
-
Train the ML to a certain accuracy.
- train(double, boolean) - Method in interface org.encog.ensemble.EnsembleML
-
Train the ML to a certain accuracy.
- train(double, boolean) - Method in class org.encog.ensemble.GenericEnsembleML
-
- train(double) - Method in class org.encog.ensemble.GenericEnsembleML
-
- Train - Interface in org.encog.neural.networks.training
-
This is an alias class for Encog 2.5 compatibility.
- TrainAdaline - Class in org.encog.neural.networks.training.simple
-
Train an ADALINE neural network.
- TrainAdaline(BasicNetwork, MLDataSet, double) - Constructor for class org.encog.neural.networks.training.simple.TrainAdaline
-
Construct an ADALINE trainer.
- TrainBasicPNN - Class in org.encog.neural.networks.training.pnn
-
Train a PNN.
- TrainBasicPNN(BasicPNN, MLDataSet) - Constructor for class org.encog.neural.networks.training.pnn.TrainBasicPNN
-
Train a BasicPNN.
- TrainBaumWelch - Class in org.encog.ml.hmm.train.bw
-
Baum Welch Learning allows a HMM to be constructed from a series of sequence
observations.
- TrainBaumWelch(HiddenMarkovModel, MLSequenceSet) - Constructor for class org.encog.ml.hmm.train.bw.TrainBaumWelch
-
- TrainBaumWelchScaled - Class in org.encog.ml.hmm.train.bw
-
Baum Welch Learning allows a HMM to be constructed from a series of sequence
observations.
- TrainBaumWelchScaled(HiddenMarkovModel, MLSequenceSet) - Constructor for class org.encog.ml.hmm.train.bw.TrainBaumWelchScaled
-
- TrainBayesian - Class in org.encog.ml.bayesian.training
-
Train a Bayesian network.
- TrainBayesian(BayesianNetwork, MLDataSet, int) - Constructor for class org.encog.ml.bayesian.training.TrainBayesian
-
Construct a Bayesian trainer.
- TrainBayesian(BayesianNetwork, MLDataSet, int, BayesianInit, BayesSearch, BayesEstimator) - Constructor for class org.encog.ml.bayesian.training.TrainBayesian
-
Construct a Bayesian trainer.
- TrainBayesianFactory - Class in org.encog.ml.factory.train
-
- TrainBayesianFactory() - Constructor for class org.encog.ml.factory.train.TrainBayesianFactory
-
- trainConsole(BasicNetwork, MLDataSet, int) - Static method in class org.encog.util.simple.EncogUtility
-
Train the neural network, using SCG training, and output status to the
console.
- trainConsole(MLTrain, BasicNetwork, MLDataSet, int) - Static method in class org.encog.util.simple.EncogUtility
-
Train the network, using the specified training algorithm, and send the
output to the console.
- trainDialog(MLTrain, BasicNetwork, MLDataSet) - Static method in class org.encog.platformspecific.j2se.TrainingDialog
-
Train, using the specified training method, display progress to a dialog
box.
- trainDialog(BasicNetwork, MLDataSet) - Static method in class org.encog.platformspecific.j2se.TrainingDialog
-
Train using SCG and display progress to a dialog box.
- TrainEA - Class in org.encog.ml.ea.train.basic
-
Provides a MLTrain compatible class that can be used to train genomes.
- TrainEA(Population, CalculateScore) - Constructor for class org.encog.ml.ea.train.basic.TrainEA
-
Create a trainer for a score function.
- TrainEA(Population, MLDataSet) - Constructor for class org.encog.ml.ea.train.basic.TrainEA
-
Create a trainer for training data.
- trainFactory - Variable in class org.encog.ensemble.Ensemble
-
- TrainGaussian - Class in org.encog.ml.fitting.gaussian
-
- TrainGaussian(GaussianFitting, MLDataSet) - Constructor for class org.encog.ml.fitting.gaussian.TrainGaussian
-
- training - Variable in class org.encog.mathutil.matrices.hessian.BasicHessian
-
The training data that provides the ideal values.
- TrainingContinuation - Class in org.encog.neural.networks.training.propagation
-
Allows training to be continued.
- TrainingContinuation() - Constructor for class org.encog.neural.networks.training.propagation.TrainingContinuation
-
- TrainingDialog - Class in org.encog.platformspecific.j2se
-
Display a training dialog.
- TrainingDialog() - Constructor for class org.encog.platformspecific.j2se.TrainingDialog
-
Construct the training dialog.
- TrainingError - Exception in org.encog.neural.networks.training
-
Thrown when a training error occurs.
- TrainingError(String) - Constructor for exception org.encog.neural.networks.training.TrainingError
-
Construct a message exception.
- TrainingError(Throwable) - Constructor for exception org.encog.neural.networks.training.TrainingError
-
Construct an exception that holds another exception.
- TrainingImplementationType - Enum in org.encog.ml
-
Specifies the type of training that an object provides.
- TrainingJob - Class in org.encog.neural.networks.training.concurrent.jobs
-
Base class for all concurrent training jobs.
- TrainingJob(BasicNetwork, MLDataSet, boolean) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
-
Construct a training job.
- TrainingSetScore - Class in org.encog.neural.networks.training
-
Calculate a score based on a training set.
- TrainingSetScore(MLDataSet) - Constructor for class org.encog.neural.networks.training.TrainingSetScore
-
Construct a training set score calculation.
- TrainingSetUtil - Class in org.encog.util.simple
-
- TrainingSetUtil() - Constructor for class org.encog.util.simple.TrainingSetUtil
-
- trainingToArray(MLDataSet) - Static method in class org.encog.util.simple.TrainingSetUtil
-
- TrainInstar - Class in org.encog.neural.cpn.training
-
Used for Instar training of a CPN neural network.
- TrainInstar(CPN, MLDataSet, double, boolean) - Constructor for class org.encog.neural.cpn.training.TrainInstar
-
Construct the instar training object.
- TrainKMeans - Class in org.encog.ml.hmm.train.kmeans
-
Train a Hidden Markov Model (HMM) with the KMeans algorithm.
- TrainKMeans(HiddenMarkovModel, MLSequenceSet) - Constructor for class org.encog.ml.hmm.train.kmeans.TrainKMeans
-
- TrainLinearRegression - Class in org.encog.ml.fitting.linear
-
- TrainLinearRegression(LinearRegression, MLDataSet) - Constructor for class org.encog.ml.fitting.linear.TrainLinearRegression
-
- TrainOutstar - Class in org.encog.neural.cpn.training
-
Used for Instar training of a CPN neural network.
- TrainOutstar(CPN, MLDataSet, double) - Constructor for class org.encog.neural.cpn.training.TrainOutstar
-
Construct the outstar trainer.
- trainPattern(MLData) - Method in class org.encog.neural.som.training.basic.BasicTrainSOM
-
Train the specified pattern.
- trainStep() - Method in class org.encog.ensemble.bagging.Bagging
-
- trainStep() - Method in interface org.encog.ensemble.EnsembleML
-
- trainStep() - Method in class org.encog.ensemble.GenericEnsembleML
-
- trainStep() - Method in class org.encog.ensemble.stacking.Stacking
-
- trainToError(MLMethod, MLDataSet, double) - Static method in class org.encog.util.simple.EncogUtility
-
Train the method, to a specific error, send the output to the console.
- trainToError(MLTrain, double) - Static method in class org.encog.util.simple.EncogUtility
-
Train to a specific error, using the specified training method, send the
output to the console.
- Trans - Class in org.encog.ca.program.generic
-
- Trans(UniverseCellFactory, int, double[]) - Constructor for class org.encog.ca.program.generic.Trans
-
- transpose(Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Return the transposition of a matrix.
- traverse(TreeNode, TreeTraversalTask) - Method in class org.encog.ml.tree.traverse.DepthFirstTraversal
-
Traverse the tree.
- traverse(TreeNode, TreeTraversalTask) - Method in interface org.encog.ml.tree.traverse.TreeTraversal
-
Traverse the tree.
- TreeNode - Interface in org.encog.ml.tree
-
A node for a tree.
- TreeTraversal - Interface in org.encog.ml.tree.traverse
-
Defines a method for traversing a tree.
- TreeTraversalTask - Interface in org.encog.ml.tree.traverse
-
A task used to traverse the tree.
- TruncationSelection - Class in org.encog.ml.ea.opp.selection
-
Truncation selection chooses a random genome from the top genomes in the
population.
- TruncationSelection(EvolutionaryAlgorithm, double) - Constructor for class org.encog.ml.ea.opp.selection.TruncationSelection
-
Construct the truncation selector.
- twoPassesNeeded() - Method in class org.encog.util.normalize.DataNormalization
-
- TYPE - Static variable in class org.encog.persist.PersistConst
-
Type.
- TYPE_ANNEAL - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Use simulated annealing.
- TYPE_ART1 - Static variable in class org.encog.persist.PersistConst
-
An ART1 neural network.
- TYPE_BACKPROP - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for backprop training.
- TYPE_BAM - Static variable in class org.encog.persist.PersistConst
-
A BAM neural network.
- TYPE_BASIC_NETWORK - Static variable in class org.encog.persist.PersistConst
-
A neural network.
- TYPE_BASIC_SPECIES - Static variable in class org.encog.persist.PersistConst
-
A species.
- TYPE_BAYESIAN - Static variable in class org.encog.ml.factory.MLMethodFactory
-
String constant for a bayesian neural network.
- TYPE_BAYESIAN - Static variable in class org.encog.ml.factory.MLTrainFactory
-
K2 training for Bayesian.
- TYPE_BOLTZMANN - Static variable in class org.encog.persist.PersistConst
-
A Boltzmann machine.
- TYPE_CPPN - Static variable in class org.encog.neural.neat.PersistNEATPopulation
-
Type for the Compositional pattern-producing networks used by HyperNEAT.
- TYPE_EPL - Static variable in class org.encog.ml.factory.MLMethodFactory
-
A Encog program.
- TYPE_EPL_GA - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for LMA training.
- TYPE_FEEDFORWARD - Static variable in class org.encog.ml.factory.MLMethodFactory
-
String constant for feedforward neural networks.
- TYPE_GENETIC - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Genetic training.
- TYPE_HOPFIELD - Static variable in class org.encog.persist.PersistConst
-
A Hopfield neural network.
- TYPE_LMA - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for LMA training.
- TYPE_LOGGING - Static variable in interface org.encog.plugin.EncogPluginBase
-
- TYPE_MANHATTAN - Static variable in class org.encog.ml.factory.MLTrainFactory
-
Manhattan training.
- TYPE_NEAT - Static variable in class org.encog.ml.factory.MLMethodFactory
-
A NEAT neural network.
- TYPE_NEAT - Static variable in class org.encog.persist.PersistConst
-
A NEAT neural network.
- TYPE_NEAT_GA - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for LMA training.
- TYPE_NEAT_GENOME - Static variable in class org.encog.persist.PersistConst
-
NEAT genome.
- TYPE_NEAT_INNOVATION - Static variable in class org.encog.persist.PersistConst
-
NEAT innovation.
- TYPE_NEAT_NEURON_GENE - Static variable in class org.encog.persist.PersistConst
-
A neuron gene.
- TYPE_NEAT_POPULATION - Static variable in class org.encog.persist.PersistConst
-
A NEAT population.
- TYPE_NELDER_MEAD - Static variable in class org.encog.ml.factory.MLTrainFactory
-
K2 training for Bayesian.
- TYPE_PNN - Static variable in class org.encog.ml.factory.MLMethodFactory
-
A probabilistic neural network.
- TYPE_PNN - Static variable in class org.encog.ml.factory.MLTrainFactory
-
PNN training.
- TYPE_PSO - Static variable in class org.encog.ml.factory.MLTrainFactory
-
- TYPE_QPROP - Static variable in class org.encog.ml.factory.MLTrainFactory
-
QPROP training.
- TYPE_RBF_NETWORK - Static variable in class org.encog.persist.PersistConst
-
A RBF network.
- TYPE_RBFNETWORK - Static variable in class org.encog.ml.factory.MLMethodFactory
-
String constant for RBF neural networks.
- TYPE_RPROP - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for RPROP training.
- TYPE_SCG - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for SCG training.
- TYPE_SERVICE - Static variable in interface org.encog.plugin.EncogPluginBase
-
- TYPE_SOM - Static variable in class org.encog.ml.factory.MLMethodFactory
-
String constant for SOMs.
- TYPE_SOM - Static variable in class org.encog.persist.PersistConst
-
A SOM neural network.
- TYPE_SOM_CLUSTER - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for SOM-Cluster training.
- TYPE_SOM_NEIGHBORHOOD - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for SOM-Neighborhood training.
- TYPE_SVD - Static variable in class org.encog.ml.factory.MLTrainFactory
-
RBF-SVD training.
- TYPE_SVM - Static variable in class org.encog.ml.factory.MLMethodFactory
-
String constant for support vector machines.
- TYPE_SVM - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for SVM training.
- TYPE_SVM - Static variable in class org.encog.persist.PersistConst
-
A support vector machine.
- TYPE_SVM_SEARCH - Static variable in class org.encog.ml.factory.MLTrainFactory
-
String constant for SVM-Search training.
- validate(String, String, String, String) - Method in class org.encog.app.analyst.script.prop.PropertyEntry
-
Validate the specified property.
- validate() - Method in class org.encog.ml.bayesian.BayesianEvent
-
Validate the event.
- validate() - Method in class org.encog.ml.bayesian.BayesianNetwork
-
Validate the structure of this Bayesian network.
- validate() - Method in class org.encog.ml.bayesian.table.BayesianTable
-
Validate the truth table.
- validate() - Method in class org.encog.neural.neat.training.NEATGenome
-
Validate the structure of this genome.
- validateAnalyzed() - Method in class org.encog.app.analyst.csv.basic.BasicFile
-
Validate that the file has been analyzed.
- validateMethodToData(MLMethod, MLDataSet) - Static method in class org.encog.util.validate.ValidateNetwork
-
- ValidateNetwork - Class in org.encog.util.validate
-
- ValidateNetwork() - Constructor for class org.encog.util.validate.ValidateNetwork
-
- validateNetworkForTraining(ContainsFlat, MLDataSet) - Static method in class org.encog.util.EncogValidate
-
Validate a network for training.
- validateNeuron(int, int) - Method in class org.encog.neural.networks.BasicNetwork
-
Validate the the specified targetLayer and neuron are valid.
- value - Variable in class org.encog.mathutil.libsvm.svm_node
-
- ValueIteration - Class in org.encog.ml.world.learning.mdp
-
- ValueIteration(World, double) - Constructor for class org.encog.ml.world.learning.mdp.ValueIteration
-
- valueOf(String) - Static method in enum org.encog.app.analyst.AnalystFileFormat
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.AnalystGoal
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.csv.sort.SortType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.script.preprocess.PreprocessAction
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.script.prop.PropertyType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.util.FieldDirection
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.wizard.NormalizeRange
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.wizard.PredictionType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.analyst.wizard.WizardMethodType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.generate.program.EncogArgType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.generate.program.NodeType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.app.generate.TargetLanguage
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.bot.browse.range.Form.Method
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ensemble.EnsembleTypes.ProblemType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.mathutil.error.ErrorCalculationMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.mathutil.rbf.RBFEnum
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.bayesian.bif.FileSection
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.bayesian.EventType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.bayesian.training.BayesianInit
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.data.market.MarketDataType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.data.temporal.TemporalDataDescription.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.data.versatile.columns.ColumnType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.hmm.alog.ForwardBackwardCalculator.Computation
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.prg.expvalue.ValueType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.prg.extension.EncogOpcodeRegistry
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.prg.extension.NodeType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.svm.KernelType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.svm.SVMType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.ml.TrainingImplementationType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.neural.neat.NEATNeuronType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.neural.neat.training.NEATInnovationType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.neural.networks.training.propagation.resilient.RPROPType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.neural.pnn.PNNKernelType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.neural.pnn.PNNOutputMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.neural.prune.NetworkPattern
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.parse.expression.ExpressionNodeType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.parse.tags.Tag.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.util.arrayutil.NormalizationAction
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.util.arrayutil.TemporalType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.encog.util.time.TimeUnit
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum org.encog.app.analyst.AnalystFileFormat
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.AnalystGoal
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.csv.sort.SortType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.script.preprocess.PreprocessAction
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.script.prop.PropertyType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.util.FieldDirection
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.wizard.NormalizeRange
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.wizard.PredictionType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.analyst.wizard.WizardMethodType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.generate.program.EncogArgType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.generate.program.NodeType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.app.generate.TargetLanguage
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.bot.browse.range.Form.Method
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ensemble.EnsembleTypes.ProblemType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.mathutil.error.ErrorCalculationMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.mathutil.rbf.RBFEnum
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.bayesian.bif.FileSection
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.bayesian.EventType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.bayesian.training.BayesianInit
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.data.market.MarketDataType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.data.temporal.TemporalDataDescription.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.data.versatile.columns.ColumnType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.hmm.alog.ForwardBackwardCalculator.Computation
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.prg.expvalue.ValueType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.prg.extension.EncogOpcodeRegistry
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.prg.extension.NodeType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.svm.KernelType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.svm.SVMType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.ml.TrainingImplementationType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.neural.neat.NEATNeuronType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.neural.neat.training.NEATInnovationType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.neural.networks.training.propagation.resilient.RPROPType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.neural.pnn.PNNKernelType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.neural.pnn.PNNOutputMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.neural.prune.NetworkPattern
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.parse.expression.ExpressionNodeType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.parse.tags.Tag.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.util.arrayutil.NormalizationAction
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.util.arrayutil.TemporalType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.encog.util.time.TimeUnit
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- ValueType - Enum in org.encog.ml.prg.expvalue
-
The type of value.
- variableExists(String) - Method in class org.encog.ml.prg.EncogProgramVariables
-
Determine if the specified variable name exists.
- VariableList - Class in org.encog.mathutil.probability.vars
-
- VariableList() - Constructor for class org.encog.mathutil.probability.vars.VariableList
-
- VariableMapping - Class in org.encog.ml.prg
-
A variable mapping defines the type for each of the variables in an Encog
program.
- VariableMapping(String, ValueType) - Constructor for class org.encog.ml.prg.VariableMapping
-
Construct a variable mapping for a non-enum type.
- VariableMapping(String, ValueType, int, int) - Constructor for class org.encog.ml.prg.VariableMapping
-
Construct a variable mapping.
- VectorAlgebra - Class in org.encog.mathutil
-
Basic vector algebra operators.
- VectorAlgebra() - Constructor for class org.encog.mathutil.VectorAlgebra
-
- vectorLength(Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath
-
Calculate the length of a vector.
- vectorProduct(double[], double[]) - Static method in class org.encog.util.EngineArray
-
Calculate the product of two vectors (a scalar value).
- VectorWindow - Class in org.encog.util.arrayutil
-
Create a sliding window of double arrays.
- VectorWindow(int) - Constructor for class org.encog.util.arrayutil.VectorWindow
-
Construct a sliding window.
- VersatileDataSource - Interface in org.encog.ml.data.versatile.sources
-
Defines a data source for the versatile data set.
- VersatileMLDataSet - Class in org.encog.ml.data.versatile
-
The versatile dataset supports several advanced features.
- VersatileMLDataSet(VersatileDataSource) - Constructor for class org.encog.ml.data.versatile.VersatileMLDataSet
-
Construct the data source.
- VERSION - Static variable in class org.encog.Encog
-
The current engog version, this should be read from the properties.
- VERSION - Static variable in class org.encog.persist.PersistConst
-
Version.
- VERYSMALL - Static variable in class org.encog.neural.som.SOM
-
Do not allow patterns to go below this very small number.
- visualize() - Method in class org.encog.ca.visualize.basic.BasicCAVisualizer
-
- visualize() - Method in interface org.encog.ca.visualize.CAVisualizer
-
- ViterbiCalculator - Class in org.encog.ml.hmm.alog
-
The Viterbi algorithm is used to find the most likely sequence of hidden
states (called the Viterbi path) that results in a sequence of observed
events.
- ViterbiCalculator(MLDataSet, HiddenMarkovModel) - Constructor for class org.encog.ml.hmm.alog.ViterbiCalculator
-
- VOLUME - Static variable in class org.encog.app.analyst.csv.basic.FileData
-
The volume.