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## org.neuroph.nnet.learning
Class DynamicBackPropagation

    java.lang.Object
      org.neuroph.core.learning.LearningRule
          org.neuroph.core.learning.IterativeLearning
              org.neuroph.core.learning.SupervisedLearning
                  org.neuroph.nnet.learning.LMS
                      org.neuroph.nnet.learning.SigmoidDeltaRule
                          org.neuroph.nnet.learning.BackPropagation
                              org.neuroph.nnet.learning.MomentumBackpropagation
                                  org.neuroph.nnet.learning.DynamicBackPropagation

All Implemented Interfaces:
  Serializable

    public class DynamicBackPropagation

extends MomentumBackpropagation

Backpropagation learning rule with dynamic learning rate and momentum

Author:
  Zoran Sevarac
See Also:
  Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class org.neuroph.nnet.learning.MomentumBackpropagation
`MomentumBackpropagation.MomentumWeightTrainingData`

Field Summary

Fields inherited from class org.neuroph.nnet.learning.MomentumBackpropagation
`momentum`

Fields inherited from class org.neuroph.core.learning.SupervisedLearning
`maxError, outputError, previousEpochError, totalNetworkError, totalSquaredErrorSum`

Fields inherited from class org.neuroph.core.learning.IterativeLearning
`currentIteration, iterationsLimited, learningRate, maxIterations`

Fields inherited from class org.neuroph.core.learning.LearningRule
`listeners, neuralNetwork`

Constructor Summary
`DynamicBackPropagation()`

Method Summary
`protected void` | `adjustLearningRate()`
`protected void` | `adjustMomentum()`
`void` | `doLearningEpoch(DataSet trainingSet)` This method implements basic logic for one learning epoch for the supervised learning algorithms.
`double` | `getLearningRateChange()`
`double` | `getMaxLearningRate()`
`double` | `getMaxMomentum()`
`double` | `getMinLearningRate()`
`double` | `getMinMomentum()`
`double` | `getMomentumChange()`
`boolean` | `getUseDynamicLearningRate()`
`boolean` | `getUseDynamicMomentum()`
`void` | `setLearningRateChange(double learningRateChange)`
`void` | `setMaxLearningRate(double maxLearningRate)`
`void` | `setMaxMomentum(double maxMomentum)`
`void` | `setMinLearningRate(double minLearningRate)`
`void` | `setMinMomentum(double minMomentum)`
`void` | `setMomentumChange(double momentumChange)`
`void` | `setUseDynamicLearningRate(boolean useDynamicLearningRate)`
`void` | `setUseDynamicMomentum(boolean useDynamicMomentum)`

Methods inherited from class org.neuroph.nnet.learning.MomentumBackpropagation
`getMomentum, onStart, setMomentum, updateNeuronWeights`

Methods inherited from class org.neuroph.nnet.learning.BackPropagation
`calculateErrorAndUpdateHiddenNeurons, calculateHiddenNeuronError, updateNetworkWeights`

Methods inherited from class org.neuroph.nnet.learning.SigmoidDeltaRule
`calculateErrorAndUpdateOutputNeurons`

Methods inherited from class org.neuroph.core.learning.SupervisedLearning
`addToSquaredErrorSum, afterEpoch, beforeEpoch, calculateOutputError, doBatchWeightsUpdate, errorChangeStalled, getMaxError, getMinErrorChange, getMinErrorChangeIterationsCount, getMinErrorChangeIterationsLimit, getPreviousEpochError, getTotalNetworkError, hasReachedStopCondition, isInBatchMode, learn, learn, learnPattern, setBatchMode, setMaxError, setMinErrorChange, setMinErrorChangeIterationsLimit`

Methods inherited from class org.neuroph.core.learning.IterativeLearning
`doOneLearningIteration, getCurrentIteration, getLearningRate, isPausedLearning, learn, learn, pause, resume, setLearningRate, setMaxIterations`

Methods inherited from class org.neuroph.core.learning.LearningRule
`addListener, fireLearningEvent, getNeuralNetwork, getTrainingSet, isStopped, removeListener, setNeuralNetwork, setTrainingSet, stopLearning`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### DynamicBackPropagation

    public DynamicBackPropagation()

Method Detail

### adjustLearningRate

    protected void adjustLearningRate()

### adjustMomentum

    protected void adjustMomentum()

### doLearningEpoch

    public void doLearningEpoch(DataSet trainingSet)

  Description copied from class: `SupervisedLearning`
  This 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:
    `doLearningEpoch` in class `SupervisedLearning`
  Parameters:
    `trainingSet` - training set for training network

### getLearningRateChange

    public double getLearningRateChange()

### setLearningRateChange

    public void setLearningRateChange(double learningRateChange)

### getMaxLearningRate

    public double getMaxLearningRate()

### setMaxLearningRate

    public void setMaxLearningRate(double maxLearningRate)

### getMaxMomentum

    public double getMaxMomentum()

### setMaxMomentum

    public void setMaxMomentum(double maxMomentum)

### getMinLearningRate

    public double getMinLearningRate()

### setMinLearningRate

    public void setMinLearningRate(double minLearningRate)

### getMinMomentum

    public double getMinMomentum()

### setMinMomentum

    public void setMinMomentum(double minMomentum)

### getMomentumChange

    public double getMomentumChange()

### setMomentumChange

    public void setMomentumChange(double momentumChange)

### getUseDynamicLearningRate

    public boolean getUseDynamicLearningRate()

### setUseDynamicLearningRate

    public void setUseDynamicLearningRate(boolean useDynamicLearningRate)

### getUseDynamicMomentum

    public boolean getUseDynamicMomentum()

### setUseDynamicMomentum

    public void setUseDynamicMomentum(boolean useDynamicMomentum)

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