org.neuroph.core.learning

Class IterativeLearning

java.lang.Object

org.neuroph.core.learning.LearningRule

org.neuroph.core.learning.IterativeLearning

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

SupervisedLearning, UnsupervisedLearning

public abstract class IterativeLearning
extends LearningRule
implements java.io.Serializable

Base class for all iterative learning algorithms. It provides the iterative learning procedure for all of its subclasses.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
IterativeLearning() Creates new instance of IterativeLearning learning algorithm

Method Summary

Modifier and Type	Method and Description
abstract void	doLearningEpoch(DataSet trainingSet) Override this method to implement specific learning epoch - one learning iteration, one pass through whole training set
void	doOneLearningIteration(DataSet trainingSet) Runs one learning iteration with the specified training set and fires event to notify observers.
int	getCurrentIteration() Returns current iteration of this learning algorithm
double	getLearningRate() Returns learning rate for this algorithm
int	getMaxIterations() Returns max iterations limit of this learning algorithm
boolean	isIterationsLimited()
boolean	isPausedLearning() Returns true if learning thread is paused, false otherwise
void	learn(DataSet trainingSet) Override this method to implement specific learning procedures
void	learn(DataSet trainingSet, int maxIterations) Trains network for the specified training set and number of iterations
void	pause() Pause the learning
void	resume() Resumes the paused learning
void	setLearningRate(double learningRate) Sets learning rate for this algorithm
void	setMaxIterations(int maxIterations) Sets iteration limit for this learning algorithm

Methods inherited from class org.neuroph.core.learning.LearningRule

addListener, getNeuralNetwork, getTrainingSet, isStopped, removeListener, setNeuralNetwork, setTrainingSet, stopLearning

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

IterativeLearning

public IterativeLearning()

Creates new instance of IterativeLearning learning algorithm

Method Detail

getLearningRate

public double getLearningRate()

Returns learning rate for this algorithm

Returns:

learning rate for this algorithm

setLearningRate

public void setLearningRate(double learningRate)

Sets learning rate for this algorithm

Parameters:

learningRate - learning rate for this algorithm

setMaxIterations

public void setMaxIterations(int maxIterations)

Sets iteration limit for this learning algorithm

Parameters:

maxIterations - iteration limit for this learning algorithm

getMaxIterations

public int getMaxIterations()

Returns max iterations limit of this learning algorithm

Returns:

max iteration limit of this learning algorithm

isIterationsLimited

public boolean isIterationsLimited()

getCurrentIteration

public int getCurrentIteration()

Returns current iteration of this learning algorithm

Returns:

current iteration of this learning algorithm

isPausedLearning

public boolean isPausedLearning()

Returns true if learning thread is paused, false otherwise

Returns:

true if learning thread is paused, false otherwise

pause

public final void pause()

Pause the learning

resume

public final void resume()

Resumes the paused learning

learn

public final void learn(DataSet trainingSet)

Description copied from class: LearningRule

Override this method to implement specific learning procedures

Specified by:

learn in class LearningRule

Parameters:

trainingSet - training set

learn

public void learn(DataSet trainingSet,
                  int maxIterations)

Trains network for the specified training set and number of iterations

Parameters:

trainingSet - training set to learn

maxIterations - maximum numberof iterations to learn

doOneLearningIteration

public void doOneLearningIteration(DataSet trainingSet)

Runs one learning iteration with the specified training set and fires event to notify observers. This method does the the doLearningEpoch() and in addtion notifes observrs when iteration is done.

Parameters:

trainingSet - training set to learn

doLearningEpoch

public abstract void doLearningEpoch(DataSet trainingSet)

Override this method to implement specific learning epoch - one learning iteration, one pass through whole training set

Parameters:

trainingSet - training set