net.sourceforge.jabm.learning
Class WidrowHoffLearner

java.lang.Object
  net.sourceforge.jabm.learning.AbstractLearner
      net.sourceforge.jabm.learning.WidrowHoffLearner

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, ContinuousLearner, Learner, MimicryLearner, Prototypeable

Direct Known Subclasses:

WidrowHoffLearnerWithMomentum

public class WidrowHoffLearner
extends AbstractLearner
implements MimicryLearner, Prototypeable, java.io.Serializable

An implementation of the Widrow-Hoff learning algorithm for 1-dimensional training sets.

See Also:

Serialized Form

Field Summary

protected double	currentOutput The current output level.
static double	DEFAULT_LEARNING_RATE
protected double	delta The current amount of adjustment to the output.
protected double	learningRate The learning rate.
protected cern.jet.random.AbstractContinousDistribution	randomParamDistribution

Fields inherited from class net.sourceforge.jabm.learning.AbstractLearner

monitor

Constructor Summary

WidrowHoffLearner()

WidrowHoffLearner(cern.jet.random.AbstractContinousDistribution randomParamDistribution)

WidrowHoffLearner(double learningRate, cern.jet.random.AbstractContinousDistribution randomParamDistribution)

WidrowHoffLearner(double learningRate, cern.jet.random.engine.RandomEngine prng)

Method Summary

double	act() Generate an output from the learning algorithm.
double	delta(double target)
void	dumpState(DataWriter out) Write out our state data to the specified data writer.
double	getCurrentOutput()
double	getDelta()
double	getLearningDelta() Return a value indicative of the amount of learning that occured during the last iteration.
double	getLearningRate()
cern.jet.random.AbstractContinousDistribution	getRandomParamDistribution()
void	initialise()
java.lang.Object	protoClone()
void	randomInitialise() Initialise with random values for free parameters
void	reset()
void	setLearningRate(double learningRate)
void	setOutputLevel(double currentOutput) Initialise the learning algorithm to output the supplied value.
void	setRandomParamDistribution(cern.jet.random.AbstractContinousDistribution randomParamDistribution)
java.lang.String	toString()
void	train(double target) Provide a training signal to the learning algorithm.

Methods inherited from class net.sourceforge.jabm.learning.AbstractLearner

monitor

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface net.sourceforge.jabm.learning.Learner

monitor

Field Detail

learningRate

protected double learningRate

The learning rate.

currentOutput

protected double currentOutput

The current output level.

delta

protected double delta

The current amount of adjustment to the output.

randomParamDistribution

protected cern.jet.random.AbstractContinousDistribution randomParamDistribution

DEFAULT_LEARNING_RATE

public static final double DEFAULT_LEARNING_RATE

See Also:

Constant Field Values

Constructor Detail

WidrowHoffLearner

public WidrowHoffLearner(double learningRate,
                         cern.jet.random.AbstractContinousDistribution randomParamDistribution)

WidrowHoffLearner

public WidrowHoffLearner(cern.jet.random.AbstractContinousDistribution randomParamDistribution)

WidrowHoffLearner

public WidrowHoffLearner()

WidrowHoffLearner

public WidrowHoffLearner(double learningRate,
                         cern.jet.random.engine.RandomEngine prng)

Method Detail

initialise

public void initialise()

protoClone

public java.lang.Object protoClone()

Specified by:

protoClone in interface Prototypeable

act

public double act()

Description copied from interface: ContinuousLearner

Generate an output from the learning algorithm.

Specified by:

act in interface ContinuousLearner

train

public void train(double target)

Description copied from interface: MimicryLearner

Provide a training signal to the learning algorithm.

Specified by:

train in interface MimicryLearner

delta

public double delta(double target)

setOutputLevel

public void setOutputLevel(double currentOutput)

Description copied from interface: MimicryLearner

Initialise the learning algorithm to output the supplied value.

Specified by:

setOutputLevel in interface MimicryLearner

dumpState

public void dumpState(DataWriter out)

Description copied from interface: Learner

Write out our state data to the specified data writer.

Specified by:

dumpState in interface Learner

Specified by:

dumpState in class AbstractLearner

getLearningDelta

public double getLearningDelta()

Description copied from interface: Learner

Return a value indicative of the amount of learning that occured during the last iteration. Values close to 0.0 indicate that the learner has converged to an equilibrium state.

Specified by:

getLearningDelta in interface Learner

Specified by:

getLearningDelta in class AbstractLearner

Returns:

A double representing the amount of learning that occured.

reset

public void reset()

setLearningRate

public void setLearningRate(double learningRate)

getLearningRate

public double getLearningRate()

randomInitialise

public void randomInitialise()

Description copied from interface: MimicryLearner

Initialise with random values for free parameters

Specified by:

randomInitialise in interface MimicryLearner

getCurrentOutput

public double getCurrentOutput()

getDelta

public double getDelta()

getRandomParamDistribution

public cern.jet.random.AbstractContinousDistribution getRandomParamDistribution()

setRandomParamDistribution

public void setRandomParamDistribution(cern.jet.random.AbstractContinousDistribution randomParamDistribution)

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object