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## org.neuroph.nnet.learning
Class SupervisedHebbianLearning

    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.SupervisedHebbianLearning

All Implemented Interfaces:
  Serializable

    public class SupervisedHebbianLearning

extends LMS

Supervised hebbian learning rule.

Author:
  Zoran Sevarac
See Also:
  Serialized Form

Field Summary

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
`SupervisedHebbianLearning()` Creates new instance of SupervisedHebbianLearning algorithm

Method Summary
`protected void` | `learnPattern(DataSetRow trainingSetRow)` Trains network with the pattern from the specified training element
`protected void` | `updateNetworkWeights(double[] desiredOutput)` This method implements weight update procedure for the whole network for this learning rule
`protected void` | `updateNeuronWeights(Neuron neuron, double desiredOutput)` This method implements weights update procedure for the single neuron

Methods inherited from class org.neuroph.nnet.learning.LMS
`updateNeuronWeights`

Methods inherited from class org.neuroph.core.learning.SupervisedLearning
`addToSquaredErrorSum, afterEpoch, beforeEpoch, calculateOutputError, doBatchWeightsUpdate, doLearningEpoch, errorChangeStalled, getMaxError, getMinErrorChange, getMinErrorChangeIterationsCount, getMinErrorChangeIterationsLimit, getPreviousEpochError, getTotalNetworkError, hasReachedStopCondition, isInBatchMode, learn, learn, onStart, 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

### SupervisedHebbianLearning

    public SupervisedHebbianLearning()

  Creates new instance of SupervisedHebbianLearning algorithm

Method Detail

### learnPattern

    protected void learnPattern(DataSetRow trainingSetRow)

  Trains network with the pattern from the specified training element

  Overrides:
    `learnPattern` in class `SupervisedLearning`
  Parameters:
    `trainingSetRow` - a single data set row to learn which contains input and desired output patterns (arrays)

### updateNetworkWeights

    protected void updateNetworkWeights(double[] desiredOutput)

  This method implements weight update procedure for the whole network for this learning rule

  Overrides:
    `updateNetworkWeights` in class `LMS`
  Parameters:
    `desiredOutput` - desired network output
  See Also:
    `SupervisedLearning.calculateOutputError(double[], double[])`, `learnPattern`

### updateNeuronWeights

    protected void updateNeuronWeights(Neuron neuron,
                                       double desiredOutput)

  This method implements weights update procedure for the single neuron

  Parameters:
    `neuron` - neuron to update weights desiredOutput desired output of the neuron

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