org.neuroph.nnet.learning
Class SigmoidDeltaRule
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
- All Implemented Interfaces:
- Serializable
- Direct Known Subclasses:
- BackPropagation
public class SigmoidDeltaRule
- extends LMS
Delta rule learning algorithm for perceptrons with sigmoid (or any other diferentiable continuous) functions.
TODO: Rename to DeltaRuleContinuous (ContinuousDeltaRule) or something like that, but that will break backward compatibility,
posibly with backpropagation which is the most used
- Author:
- Zoran Sevarac
- See Also:
LMS
,
Serialized Form
Method Summary |
protected void |
calculateErrorAndUpdateOutputNeurons(double[] outputError)
This method implements weights update procedure for the output neurons
Calculates delta/error and calls updateNeuronWeights to update neuron's weights
for each output neuron |
protected void |
updateNetworkWeights(double[] outputError)
This method implements weight update procedure for the whole network for
this learning rule |
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, learnPattern, onStart, setBatchMode, setMaxError, setMinErrorChange, setMinErrorChangeIterationsLimit |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
SigmoidDeltaRule
public SigmoidDeltaRule()
- Creates new SigmoidDeltaRule
updateNetworkWeights
protected void updateNetworkWeights(double[] outputError)
- This method implements weight update procedure for the whole network for
this learning rule
- Overrides:
updateNetworkWeights
in class LMS
- Parameters:
outputError
- output error vector- See Also:
SupervisedLearning.calculateOutputError(double[], double[])
,
learnPattern
calculateErrorAndUpdateOutputNeurons
protected void calculateErrorAndUpdateOutputNeurons(double[] outputError)
- This method implements weights update procedure for the output neurons
Calculates delta/error and calls updateNeuronWeights to update neuron's weights
for each output neuron
- Parameters:
outputError
- error vector for output neurons
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