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

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

Method Summary

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 final void createTrainer(boolean singleThreaded)

Create a trainer to use.

Specified by:

createTrainer in class TrainingJob

getInitialUpdate

public final double getInitialUpdate()

Returns:

the initialUpdate

getMaxStep

public final double getMaxStep()

Returns:

the maxStep

setInitialUpdate

public final void setInitialUpdate(double initialUpdate)

Parameters:

initialUpdate - the initialUpdate to set

setMaxStep

public final void setMaxStep(double maxStep)

Parameters:

maxStep - the maxStep to set