Modifier and Type | Method and Description |
---|---|
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.
|
Modifier and Type | Method and Description |
---|---|
MLTrain |
EnsembleML.getTraining() |
MLTrain |
GenericEnsembleML.getTraining() |
MLTrain |
EnsembleTrainFactory.getTraining(MLMethod method,
MLDataSet trainingData) |
Modifier and Type | Method and Description |
---|---|
void |
EnsembleML.setTraining(MLTrain train)
Set the training for this member
|
void |
GenericEnsembleML.setTraining(MLTrain train) |
Modifier and Type | Method and Description |
---|---|
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) |
Modifier and Type | Class and Description |
---|---|
class |
TrainBayesian
Train a Bayesian network.
|
Modifier and Type | Class and Description |
---|---|
class |
TrainEA
Provides a MLTrain compatible class that can be used to train genomes.
|
Modifier and Type | Method and Description |
---|---|
MLTrain |
MLTrainFactory.create(MLMethod method,
MLDataSet training,
String type,
String args)
Create a trainer.
|
Modifier and Type | Method and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
TrainGaussian |
Modifier and Type | Class and Description |
---|---|
class |
TrainLinearRegression |
Modifier and Type | Class and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
TrainKMeans
Train a Hidden Markov Model (HMM) with the KMeans algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
SVMSearchTrain
Provides training for Support Vector Machine networks.
|
class |
SVMTrain
Provides training for Support Vector Machine networks.
|
Modifier and Type | Class and Description |
---|---|
class |
BasicTraining
An abstract class that implements basic training for most training
algorithms.
|
Modifier and Type | Method and Description |
---|---|
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.
|
Constructor and Description |
---|
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.
|
Modifier and Type | Method and Description |
---|---|
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.
|
void |
SimpleEarlyStoppingStrategy.init(MLTrain theTrain)
Initialize this strategy.
|
Modifier and Type | Class and Description |
---|---|
class |
TrainInstar
Used for Instar training of a CPN neural network.
|
class |
TrainOutstar
Used for Instar training of a CPN neural network.
|
Modifier and Type | Class and Description |
---|---|
class |
FreeformBackPropagation
Perform backpropagation for a freeform neural network.
|
class |
FreeformPropagationTraining
Provides basic propagation functions to other trainers.
|
class |
FreeformResilientPropagation |
Modifier and Type | Interface and Description |
---|---|
interface |
Train
This is an alias class for Encog 2.5 compatibility.
|
Modifier and Type | Class and Description |
---|---|
class |
NeuralSimulatedAnnealing
This class implements a simulated annealing training algorithm for neural
networks.
|
Modifier and Type | Method and Description |
---|---|
MLTrain |
TrainingJob.getTrain() |
Modifier and Type | Method and Description |
---|---|
void |
TrainingJob.setTrain(MLTrain train) |
Modifier and Type | Class and Description |
---|---|
class |
CrossTraining
Base class for cross training trainers.
|
class |
CrossValidationKFold
Train using K-Fold cross validation.
|
Constructor and Description |
---|
CrossValidationKFold(MLTrain train,
int k)
Construct a cross validation trainer.
|
Modifier and Type | Class and Description |
---|---|
class |
LevenbergMarquardtTraining
Trains a neural network using a Levenberg Marquardt algorithm (LMA).
|
Modifier and Type | Class and Description |
---|---|
class |
NelderMeadTraining
The Nelder-Mead method is a commonly used parameter optimization method that
can be used for neural network training.
|
Modifier and Type | Class and Description |
---|---|
class |
TrainBasicPNN
Train a PNN.
|
Modifier and Type | Class and Description |
---|---|
class |
Propagation
Implements basic functionality that is needed by each of the propagation
methods.
|
Modifier and Type | Class and Description |
---|---|
class |
Backpropagation
This class implements a backpropagation training algorithm for feed forward
neural networks.
|
Modifier and Type | Class and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
QuickPropagation
QPROP is an efficient training method that is based on Newton's Method.
|
Modifier and Type | Class and Description |
---|---|
class |
ResilientPropagation
One problem with the backpropagation algorithm is that the magnitude of the
partial derivative is usually too large or too small.
|
Modifier and Type | Class and Description |
---|---|
class |
ScaledConjugateGradient
This is a training class that makes use of scaled conjugate gradient methods.
|
Modifier and Type | Class and Description |
---|---|
class |
NeuralPSO
Iteratively trains a population of neural networks by applying
particle swarm optimisation (PSO).
|
Modifier and Type | Class and Description |
---|---|
class |
TrainAdaline
Train an ADALINE neural network.
|
Modifier and Type | Method and Description |
---|---|
void |
RegularizationStrategy.init(MLTrain train) |
void |
SmartLearningRate.init(MLTrain train)
Initialize this strategy.
|
void |
SmartMomentum.init(MLTrain train)
Initialize this strategy.
|
Modifier and Type | Class and Description |
---|---|
class |
SVDTraining
Train a RBF neural network using a SVD.
|
Modifier and Type | Class and Description |
---|---|
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).
|
Modifier and Type | Class and Description |
---|---|
class |
SOMClusterCopyTraining
SOM cluster copy is a very simple trainer for SOM's.
|
Modifier and Type | Method and Description |
---|---|
static void |
TrainingDialog.trainDialog(MLTrain train,
BasicNetwork network,
MLDataSet trainingSet)
Train, using the specified training method, display progress to a dialog
box.
|
Modifier and Type | Method and Description |
---|---|
MLTrain |
EncogPluginService1.createTraining(MLMethod method,
MLDataSet training,
String type,
String args)
Create a trainer.
|
Modifier and Type | Method and Description |
---|---|
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.
|
Modifier and Type | Method and Description |
---|---|
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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