org.neuroph.nnet.learning
Class DynamicBackPropagation
- java.lang.Object
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- All Implemented Interfaces:
- java.io.Serializable
public class DynamicBackPropagation extends MomentumBackpropagation
Backpropagation learning rule with dynamic learning rate and momentum- See Also:
- Serialized Form
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Nested Class Summary
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Nested classes/interfaces inherited from class org.neuroph.nnet.learning.MomentumBackpropagation
MomentumBackpropagation.MomentumTrainingData
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Constructor Summary
Constructors Constructor and Description DynamicBackPropagation()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description voiddoLearningEpoch(DataSet trainingSet)This method implements basic logic for one learning epoch for the supervised learning algorithms.doublegetLearningRateChange()doublegetMaxLearningRate()doublegetMaxMomentum()doublegetMinLearningRate()doublegetMinMomentum()doublegetMomentumChange()booleangetUseDynamicLearningRate()booleangetUseDynamicMomentum()voidsetLearningRateChange(double learningRateChange)voidsetMaxLearningRate(double maxLearningRate)voidsetMaxMomentum(double maxMomentum)voidsetMinLearningRate(double minLearningRate)voidsetMinMomentum(double minMomentum)voidsetMomentumChange(double momentumChange)voidsetUseDynamicLearningRate(boolean useDynamicLearningRate)voidsetUseDynamicMomentum(boolean useDynamicMomentum)-
Methods inherited from class org.neuroph.nnet.learning.MomentumBackpropagation
getMomentum, setMomentum, updateNeuronWeights
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Methods inherited from class org.neuroph.core.learning.SupervisedLearning
getErrorFunction, getMaxError, getMinErrorChange, getMinErrorChangeIterationsCount, getMinErrorChangeIterationsLimit, getPreviousEpochError, getTotalNetworkError, isBatchMode, learn, learn, setBatchMode, setErrorFunction, setMaxError, setMinErrorChange, setMinErrorChangeIterationsLimit
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Methods inherited from class org.neuroph.core.learning.IterativeLearning
doOneLearningIteration, getCurrentIteration, getLearningRate, getMaxIterations, isIterationsLimited, isPausedLearning, learn, learn, pause, resume, setLearningRate, setMaxIterations
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Methods inherited from class org.neuroph.core.learning.LearningRule
addListener, getNeuralNetwork, getTrainingSet, isStopped, removeListener, setNeuralNetwork, setTrainingSet, stopLearning
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Method Detail
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doLearningEpoch
public void doLearningEpoch(DataSet trainingSet)
Description copied from class:SupervisedLearningThis method implements basic logic for one learning epoch for the supervised learning algorithms. Epoch is the one pass through the training set. This method iterates through the training set and trains network for each element. It also sets flag if conditions to stop learning has been reached: network error below some allowed value, or maximum iteration count- Overrides:
doLearningEpochin classSupervisedLearning- Parameters:
trainingSet- training set for training network
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getLearningRateChange
public double getLearningRateChange()
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setLearningRateChange
public void setLearningRateChange(double learningRateChange)
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getMaxLearningRate
public double getMaxLearningRate()
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setMaxLearningRate
public void setMaxLearningRate(double maxLearningRate)
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getMaxMomentum
public double getMaxMomentum()
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setMaxMomentum
public void setMaxMomentum(double maxMomentum)
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getMinLearningRate
public double getMinLearningRate()
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setMinLearningRate
public void setMinLearningRate(double minLearningRate)
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getMinMomentum
public double getMinMomentum()
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setMinMomentum
public void setMinMomentum(double minMomentum)
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getMomentumChange
public double getMomentumChange()
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setMomentumChange
public void setMomentumChange(double momentumChange)
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getUseDynamicLearningRate
public boolean getUseDynamicLearningRate()
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setUseDynamicLearningRate
public void setUseDynamicLearningRate(boolean useDynamicLearningRate)
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getUseDynamicMomentum
public boolean getUseDynamicMomentum()
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setUseDynamicMomentum
public void setUseDynamicMomentum(boolean useDynamicMomentum)
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