org.encog.neural.networks.training.concurrent.jobs

Class RPROPJob

java.lang.Object

org.encog.neural.networks.training.concurrent.jobs.TrainingJob

org.encog.neural.networks.training.concurrent.jobs.RPROPJob

public class RPROPJob
extends TrainingJob

A training definition for RPROP training.

Constructor Summary

Constructors

Constructor and Description
RPROPJob(BasicNetwork network, MLDataSet training, boolean loadToMemory) Construct an RPROP job.

Method Summary

Methods

Modifier and Type	Method and Description
void	createTrainer(boolean singleThreaded) Create a trainer to use.
double	getInitialUpdate()
double	getMaxStep()
void	setInitialUpdate(double initialUpdate)
void	setMaxStep(double maxStep)

Methods inherited from class org.encog.neural.networks.training.concurrent.jobs.TrainingJob

getError, getNetwork, getStrategies, getTrain, getTraining, isLoadToMemory, setError, setLoadToMemory, setNetwork, setTrain, setTraining, shouldContinue

Methods inherited from class java.lang.Object

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

Constructor Detail

RPROPJob

public RPROPJob(BasicNetwork network,
        MLDataSet training,
        boolean loadToMemory)

Construct an RPROP job. For more information on RPROP see the ResilientPropagation class.

Parameters:

network - The network to train.

training - The training data to use.

loadToMemory - True if binary training data should be loaded to memory.

Method Detail

createTrainer

public void createTrainer(boolean singleThreaded)

Create a trainer to use.

Specified by:

createTrainer in class TrainingJob

getInitialUpdate

public double getInitialUpdate()

Returns:

the initialUpdate

getMaxStep

public double getMaxStep()

Returns:

the maxStep

setInitialUpdate

public void setInitialUpdate(double initialUpdate)

Parameters:

initialUpdate - the initialUpdate to set

setMaxStep

public void setMaxStep(double maxStep)

Parameters:

maxStep - the maxStep to set