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
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.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 java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
SupervisedHebbianLearning
public SupervisedHebbianLearning()
- Creates new instance of SupervisedHebbianLearning algorithm
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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