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Uses of MLTrain in org.encog.app.analyst |
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Methods in org.encog.app.analyst with parameters of type MLTrain | |
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void |
EncogAnalyst.reportTraining(MLTrain train)
Report training. |
void |
ConsoleAnalystListener.reportTraining(MLTrain train)
Report progress on training. |
void |
AnalystListener.reportTraining(MLTrain train)
Report progress on training. |
Uses of MLTrain in org.encog.ensemble |
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Methods in org.encog.ensemble that return MLTrain | |
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MLTrain |
EnsembleML.getTraining()
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MLTrain |
GenericEnsembleML.getTraining()
|
MLTrain |
EnsembleTrainFactory.getTraining(MLMethod method,
MLDataSet trainingData)
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Methods in org.encog.ensemble with parameters of type MLTrain | |
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void |
EnsembleML.setTraining(MLTrain train)
Set the training for this member |
void |
GenericEnsembleML.setTraining(MLTrain train)
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Uses of MLTrain in org.encog.ensemble.training |
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Methods in org.encog.ensemble.training that return MLTrain | |
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MLTrain |
ManhattanPropagationFactory.getTraining(MLMethod mlMethod,
MLDataSet trainingData)
|
MLTrain |
ResilientPropagationFactory.getTraining(MLMethod mlMethod,
MLDataSet trainingData)
|
MLTrain |
ScaledConjugateGradientFactory.getTraining(MLMethod mlMethod,
MLDataSet trainingData)
|
MLTrain |
LevenbergMarquardtFactory.getTraining(MLMethod mlMethod,
MLDataSet trainingData)
|
MLTrain |
BackpropagationFactory.getTraining(MLMethod mlMethod,
MLDataSet trainingData)
|
Uses of MLTrain in org.encog.ml.bayesian.training |
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Classes in org.encog.ml.bayesian.training that implement MLTrain | |
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class |
TrainBayesian
Train a Bayesian network. |
Uses of MLTrain in org.encog.ml.ea.train.basic |
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Classes in org.encog.ml.ea.train.basic that implement MLTrain | |
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class |
TrainEA
Provides a MLTrain compatible class that can be used to train genomes. |
Uses of MLTrain in org.encog.ml.factory |
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Methods in org.encog.ml.factory that return MLTrain | |
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MLTrain |
MLTrainFactory.create(MLMethod method,
MLDataSet training,
String type,
String args)
Create a trainer. |
Uses of MLTrain in org.encog.ml.factory.train |
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Methods in org.encog.ml.factory.train that return MLTrain | |
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MLTrain |
GeneticFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create an annealing trainer. |
MLTrain |
SVMFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a SVM trainer. |
MLTrain |
ClusterSOMFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a cluster SOM trainer. |
MLTrain |
LMAFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a LMA trainer. |
MLTrain |
NEATGAFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create an NEAT GA trainer. |
MLTrain |
PSOFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a PSO trainer. |
MLTrain |
QuickPropFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a quick propagation trainer. |
MLTrain |
TrainBayesianFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a K2 trainer. |
MLTrain |
RBFSVDFactory.create(MLMethod method,
MLDataSet training,
String args)
Create a RBF-SVD trainer. |
MLTrain |
AnnealFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create an annealing trainer. |
MLTrain |
SCGFactory.create(MLMethod method,
MLDataSet training,
String args)
Create a SCG trainer. |
MLTrain |
NeighborhoodSOMFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a LMA trainer. |
MLTrain |
BackPropFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a backpropagation trainer. |
MLTrain |
PNNTrainFactory.create(MLMethod method,
MLDataSet training,
String args)
Create a PNN trainer. |
MLTrain |
NelderMeadFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a Nelder Mead trainer. |
MLTrain |
ManhattanFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a Manhattan trainer. |
MLTrain |
SVMSearchFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a SVM trainer. |
MLTrain |
EPLGAFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create an EPL GA trainer. |
MLTrain |
RPROPFactory.create(MLMethod method,
MLDataSet training,
String argsStr)
Create a RPROP trainer. |
Uses of MLTrain in org.encog.ml.fitting.gaussian |
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Classes in org.encog.ml.fitting.gaussian that implement MLTrain | |
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class |
TrainGaussian
|
Uses of MLTrain in org.encog.ml.fitting.linear |
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Classes in org.encog.ml.fitting.linear that implement MLTrain | |
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class |
TrainLinearRegression
|
Uses of MLTrain in org.encog.ml.genetic |
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Classes in org.encog.ml.genetic that implement MLTrain | |
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class |
MLMethodGeneticAlgorithm
Implements a genetic algorithm that allows an MLMethod that is encodable (MLEncodable) to be trained. |
class |
MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper
Very simple class that implements a genetic algorithm. |
Uses of MLTrain in org.encog.ml.hmm.train.bw |
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Classes in org.encog.ml.hmm.train.bw that implement MLTrain | |
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class |
BaseBaumWelch
This class provides the base implementation for Baum-Welch learning for HMM's. |
class |
TrainBaumWelch
Baum Welch Learning allows a HMM to be constructed from a series of sequence observations. |
class |
TrainBaumWelchScaled
Baum Welch Learning allows a HMM to be constructed from a series of sequence observations. |
Uses of MLTrain in org.encog.ml.hmm.train.kmeans |
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Classes in org.encog.ml.hmm.train.kmeans that implement MLTrain | |
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class |
TrainKMeans
Train a Hidden Markov Model (HMM) with the KMeans algorithm. |
Uses of MLTrain in org.encog.ml.svm.training |
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Classes in org.encog.ml.svm.training that implement MLTrain | |
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class |
SVMSearchTrain
Provides training for Support Vector Machine networks. |
class |
SVMTrain
Provides training for Support Vector Machine networks. |
Uses of MLTrain in org.encog.ml.train |
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Classes in org.encog.ml.train that implement MLTrain | |
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class |
BasicTraining
An abstract class that implements basic training for most training algorithms. |
Uses of MLTrain in org.encog.ml.train.strategy |
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Methods in org.encog.ml.train.strategy with parameters of type MLTrain | |
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void |
HybridStrategy.init(MLTrain train)
Initialize this strategy. |
void |
RequiredImprovementStrategy.init(MLTrain train)
Initialize this strategy. |
void |
Greedy.init(MLTrain train)
Initialize this strategy. |
void |
Strategy.init(MLTrain train)
Initialize this strategy. |
void |
StopTrainingStrategy.init(MLTrain train)
Initialize this strategy. |
void |
ResetStrategy.init(MLTrain train)
Initialize this strategy. |
Constructors in org.encog.ml.train.strategy with parameters of type MLTrain | |
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HybridStrategy(MLTrain altTrain)
Construct a hybrid strategy with the default minimum improvement and toleration cycles. |
|
HybridStrategy(MLTrain altTrain,
double minImprovement,
int tolerateMinImprovement,
int alternateCycles)
Create a hybrid strategy. |
Uses of MLTrain in org.encog.ml.train.strategy.end |
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Methods in org.encog.ml.train.strategy.end with parameters of type MLTrain | |
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void |
EarlyStoppingStrategy.init(MLTrain theTrain)
Initialize this strategy. |
void |
EndIterationsStrategy.init(MLTrain train)
Initialize this strategy. |
void |
EndMinutesStrategy.init(MLTrain train)
Initialize this strategy. |
void |
EndMaxErrorStrategy.init(MLTrain train)
Initialize this strategy. |
Uses of MLTrain in org.encog.neural.cpn.training |
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Classes in org.encog.neural.cpn.training that implement MLTrain | |
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class |
TrainInstar
Used for Instar training of a CPN neural network. |
class |
TrainOutstar
Used for Instar training of a CPN neural network. |
Uses of MLTrain in org.encog.neural.freeform.training |
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Classes in org.encog.neural.freeform.training that implement MLTrain | |
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class |
FreeformBackPropagation
|
class |
FreeformPropagationTraining
Provides basic propagation functions to other trainers. |
class |
FreeformResilientPropagation
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Uses of MLTrain in org.encog.neural.networks.training |
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Subinterfaces of MLTrain in org.encog.neural.networks.training | |
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interface |
Train
This is an alias class for Encog 2.5 compatibility. |
Uses of MLTrain in org.encog.neural.networks.training.anneal |
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Classes in org.encog.neural.networks.training.anneal that implement MLTrain | |
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class |
NeuralSimulatedAnnealing
This class implements a simulated annealing training algorithm for neural networks. |
Uses of MLTrain in org.encog.neural.networks.training.concurrent.jobs |
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Methods in org.encog.neural.networks.training.concurrent.jobs that return MLTrain | |
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MLTrain |
TrainingJob.getTrain()
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Methods in org.encog.neural.networks.training.concurrent.jobs with parameters of type MLTrain | |
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void |
TrainingJob.setTrain(MLTrain train)
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Uses of MLTrain in org.encog.neural.networks.training.cross |
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Classes in org.encog.neural.networks.training.cross that implement MLTrain | |
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class |
CrossTraining
Base class for cross training trainers. |
class |
CrossValidationKFold
Train using K-Fold cross validation. |
Constructors in org.encog.neural.networks.training.cross with parameters of type MLTrain | |
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CrossValidationKFold(MLTrain train,
int k)
Construct a cross validation trainer. |
Uses of MLTrain in org.encog.neural.networks.training.lma |
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Classes in org.encog.neural.networks.training.lma that implement MLTrain | |
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class |
LevenbergMarquardtTraining
Trains a neural network using a Levenberg Marquardt algorithm (LMA). |
Uses of MLTrain in org.encog.neural.networks.training.nm |
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Classes in org.encog.neural.networks.training.nm that implement MLTrain | |
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class |
NelderMeadTraining
The Nelder-Mead method is a commonly used parameter optimization method that can be used for neural network training. |
Uses of MLTrain in org.encog.neural.networks.training.pnn |
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Classes in org.encog.neural.networks.training.pnn that implement MLTrain | |
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class |
TrainBasicPNN
Train a PNN. |
Uses of MLTrain in org.encog.neural.networks.training.propagation |
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Classes in org.encog.neural.networks.training.propagation that implement MLTrain | |
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class |
Propagation
Implements basic functionality that is needed by each of the propagation methods. |
Uses of MLTrain in org.encog.neural.networks.training.propagation.back |
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Classes in org.encog.neural.networks.training.propagation.back that implement MLTrain | |
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class |
Backpropagation
This class implements a backpropagation training algorithm for feed forward neural networks. |
Uses of MLTrain in org.encog.neural.networks.training.propagation.manhattan |
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Classes in org.encog.neural.networks.training.propagation.manhattan that implement MLTrain | |
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class |
ManhattanPropagation
One problem that the backpropagation technique has is that the magnitude of the partial derivative may be calculated too large or too small. |
Uses of MLTrain in org.encog.neural.networks.training.propagation.quick |
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Classes in org.encog.neural.networks.training.propagation.quick that implement MLTrain | |
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class |
QuickPropagation
QPROP is an efficient training method that is based on Newton's Method. |
Uses of MLTrain in org.encog.neural.networks.training.propagation.resilient |
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Classes in org.encog.neural.networks.training.propagation.resilient that implement MLTrain | |
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class |
ResilientPropagation
One problem with the backpropagation algorithm is that the magnitude of the partial derivative is usually too large or too small. |
Uses of MLTrain in org.encog.neural.networks.training.propagation.scg |
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Classes in org.encog.neural.networks.training.propagation.scg that implement MLTrain | |
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class |
ScaledConjugateGradient
This is a training class that makes use of scaled conjugate gradient methods. |
Uses of MLTrain in org.encog.neural.networks.training.pso |
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Classes in org.encog.neural.networks.training.pso that implement MLTrain | |
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class |
NeuralPSO
Iteratively trains a population of neural networks by applying particle swarm optimisation (PSO). |
Uses of MLTrain in org.encog.neural.networks.training.simple |
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Classes in org.encog.neural.networks.training.simple that implement MLTrain | |
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class |
TrainAdaline
Train an ADALINE neural network. |
Uses of MLTrain in org.encog.neural.networks.training.strategy |
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Methods in org.encog.neural.networks.training.strategy with parameters of type MLTrain | |
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void |
RegularizationStrategy.init(MLTrain train)
|
void |
SmartLearningRate.init(MLTrain train)
Initialize this strategy. |
void |
SmartMomentum.init(MLTrain train)
Initialize this strategy. |
Uses of MLTrain in org.encog.neural.rbf.training |
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Classes in org.encog.neural.rbf.training that implement MLTrain | |
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class |
SVDTraining
Train a RBF neural network using a SVD. |
Uses of MLTrain in org.encog.neural.som.training.basic |
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Classes in org.encog.neural.som.training.basic that implement MLTrain | |
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class |
BasicTrainSOM
This class implements competitive training, which would be used in a winner-take-all neural network, such as the self organizing map (SOM). |
Uses of MLTrain in org.encog.neural.som.training.clustercopy |
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Classes in org.encog.neural.som.training.clustercopy that implement MLTrain | |
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class |
SOMClusterCopyTraining
SOM cluster copy is a very simple trainer for SOM's. |
Uses of MLTrain in org.encog.platformspecific.j2se |
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Methods in org.encog.platformspecific.j2se with parameters of type MLTrain | |
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static void |
TrainingDialog.trainDialog(MLTrain train,
BasicNetwork network,
MLDataSet trainingSet)
Train, using the specified training method, display progress to a dialog box. |
Uses of MLTrain in org.encog.plugin |
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Methods in org.encog.plugin that return MLTrain | |
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MLTrain |
EncogPluginService1.createTraining(MLMethod method,
MLDataSet training,
String type,
String args)
Create a trainer. |
Uses of MLTrain in org.encog.plugin.system |
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Methods in org.encog.plugin.system that return MLTrain | |
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MLTrain |
SystemActivationPlugin.createTraining(MLMethod method,
MLDataSet training,
String type,
String args)
Create a trainer. |
MLTrain |
SystemTrainingPlugin.createTraining(MLMethod method,
MLDataSet training,
String type,
String args)
|
MLTrain |
SystemMethodsPlugin.createTraining(MLMethod method,
MLDataSet training,
String type,
String args)
Create a trainer. |
Uses of MLTrain in org.encog.util.simple |
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Methods in org.encog.util.simple with parameters of type MLTrain | |
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static void |
EncogUtility.trainConsole(MLTrain train,
BasicNetwork network,
MLDataSet trainingSet,
int minutes)
Train the network, using the specified training algorithm, and send the output to the console. |
static void |
EncogUtility.trainToError(MLTrain train,
double error)
Train to a specific error, using the specified training method, send the output to the console. |
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