org.neuroph.contrib.bpbench

Class TrainingSettings

java.lang.Object

org.neuroph.contrib.bpbench.TrainingSettings

public class TrainingSettings
extends java.lang.Object

Holds settings for individual training

Constructor Summary

Constructors

Constructor and Description
TrainingSettings(double learningRate, double momentum, int hiddenNeurons, int maxIterations, double maxError, boolean batchMode) Create instance of training settings with given parameters

Method Summary

Modifier and Type	Method and Description
double	getDecreaseFactor() Return decrease factor for resilient propagation
int	getHiddenNeurons() Return number of neurons in hidden layer for this training
double	getIncreaseFactor() Return increase factor for resilient propagation
double	getInitialDelta() Return initial delta for resilient propagation
double	getLearningRate() Return learning rate for this training
double	getMaxDelta() Return maximum delta for resilient propagation
double	getMaxError() Return maximum total error for this training
int	getMaxIterations() Return maximum number of iterations for this training
double	getMinDelta() Return minimum delta for resilient propagation
double	getMomentum() Return momentum for this training
boolean	isBatchMode() Return batch mode state
void	setBatchMode(boolean batchMode) Set batch mode for this training
void	setDecreaseFactor(double decreaseFactor) Set decrease factor for resilient propagation
void	setHiddenNeurons(int hiddenNeurons) Set number of neurons in hidden layer for this training
void	setIncreaseFactor(double increaseFactor) Set increase factor for resilient propagation
void	setInitialDelta(double initialDelta) Set initial delta for resilient propagation
void	setLearningRate(double learningRate) Set learning rate for this training
void	setMaxDelta(double maxDelta) Set maximum delta for resilient propagation
void	setMaxError(double maxError) Set maximum total error for this training
void	setMaxIterations(int maxIterations) Set maximum number of iterations for this training
void	setMinDelta(double minDelta) Set minimum delta for resilient propagation
void	setMomentum(double momentum) Set momentum for this training

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

TrainingSettings

public TrainingSettings(double learningRate,
                        double momentum,
                        int hiddenNeurons,
                        int maxIterations,
                        double maxError,
                        boolean batchMode)

Create instance of training settings with given parameters

Parameters:

learningRate -

momentum -

hiddenNeurons -

maxIterations -

maxError -

batchMode -

Method Detail

isBatchMode

public boolean isBatchMode()

Return batch mode state

Returns:

batch mode

setBatchMode

public void setBatchMode(boolean batchMode)

Set batch mode for this training

Parameters:

batchMode -

getMaxIterations

public int getMaxIterations()

Return maximum number of iterations for this training

Returns:

maximum iterations

setMaxIterations

public void setMaxIterations(int maxIterations)

Set maximum number of iterations for this training

Parameters:

maxIterations -

getMaxError

public double getMaxError()

Return maximum total error for this training

Returns:

maximum error

setMaxError

public void setMaxError(double maxError)

Set maximum total error for this training

Parameters:

maxError -

getLearningRate

public double getLearningRate()

Return learning rate for this training

Returns:

learning rate

setLearningRate

public void setLearningRate(double learningRate)

Set learning rate for this training

Parameters:

learningRate -

getMomentum

public double getMomentum()

Return momentum for this training

Returns:

momentum

setMomentum

public void setMomentum(double momentum)

Set momentum for this training

Parameters:

momentum -

getHiddenNeurons

public int getHiddenNeurons()

Return number of neurons in hidden layer for this training

Returns:

setHiddenNeurons

public void setHiddenNeurons(int hiddenNeurons)

Set number of neurons in hidden layer for this training

Parameters:

hiddenNeurons -

getDecreaseFactor

public double getDecreaseFactor()

Return decrease factor for resilient propagation

Returns:

decrease factor

setDecreaseFactor

public void setDecreaseFactor(double decreaseFactor)

Set decrease factor for resilient propagation

Parameters:

decreaseFactor -

getIncreaseFactor

public double getIncreaseFactor()

Return increase factor for resilient propagation

Returns:

increase factor

setIncreaseFactor

public void setIncreaseFactor(double increaseFactor)

Set increase factor for resilient propagation

Parameters:

increaseFactor -

getInitialDelta

public double getInitialDelta()

Return initial delta for resilient propagation

Returns:

initial delta

setInitialDelta

public void setInitialDelta(double initialDelta)

Set initial delta for resilient propagation

Parameters:

initialDelta -

getMaxDelta

public double getMaxDelta()

Return maximum delta for resilient propagation

Returns:

maximum delta

setMaxDelta

public void setMaxDelta(double maxDelta)

Set maximum delta for resilient propagation

Parameters:

maxDelta -

getMinDelta

public double getMinDelta()

Return minimum delta for resilient propagation

Returns:

minimum delta

setMinDelta

public void setMinDelta(double minDelta)

Set minimum delta for resilient propagation

Parameters:

minDelta -