org.encog.neural.networks.training.concurrent.jobs
Class RPROPJob
- java.lang.Object
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- org.encog.neural.networks.training.concurrent.jobs.TrainingJob
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- org.encog.neural.networks.training.concurrent.jobs.RPROPJob
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public class RPROPJob extends TrainingJob
A training definition for RPROP training.
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Constructor Summary
Constructors Constructor and Description RPROPJob(BasicNetwork network, MLDataSet training, boolean loadToMemory)Construct an RPROP job.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description voidcreateTrainer(boolean singleThreaded)Create a trainer to use.doublegetInitialUpdate()doublegetMaxStep()voidsetInitialUpdate(double initialUpdate)voidsetMaxStep(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
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Constructor Detail
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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.
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Method Detail
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createTrainer
public void createTrainer(boolean singleThreaded)
Create a trainer to use.- Specified by:
createTrainerin classTrainingJob- Parameters:
singleThreaded- Whether training is single threaded
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getInitialUpdate
public double getInitialUpdate()
- Returns:
- the initialUpdate
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getMaxStep
public double getMaxStep()
- Returns:
- the maxStep
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setInitialUpdate
public void setInitialUpdate(double initialUpdate)
- Parameters:
initialUpdate- the initialUpdate to set
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setMaxStep
public void setMaxStep(double maxStep)
- Parameters:
maxStep- the maxStep to set
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