yawn.nn.fuzzyartmap
Class FuzzyArtMap

java.lang.Object
  yawn.nn.NeuralNetwork
      yawn.nn.fuzzyartmap.FuzzyArtMap

All Implemented Interfaces:

java.io.Serializable, OptimizableModel

public class FuzzyArtMap
extends NeuralNetwork
implements OptimizableModel

Implements the Fuzzy ARTMAP neural network, as described in

Carpenter, G. A., Grossberg, S., Markuzon, N., Reynolds, J. H. & Rosen, D. B. (1992). Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Transactions on Neural Networks, 3(5):698-713.

This code is based on the implementations of Relu Patrascu (rpatrasc at cs dot uwaterloo dot ca) and John Reynold (refined and maintained by Ah-Hwee Tan (atan at park dot bu dot edu)).
$Id: FuzzyArtMap.java,v 1.11 2005/04/07 17:28:25 supermarti Exp $

Version:

$Revision: 1.11 $

Author:

Luis Martí (luis dot marti at uc3m dot es)

See Also:

Serialized Form

Field Summary

protected double	alphaArtA
protected double	alphaArtB
protected FuzzyArt	artA
protected FuzzyArt	artB
protected double	betaArtA
protected double	betaArtB
protected double	epsilon small amount added when doing match tracking
protected int	inputSize
protected double	matchError max difference between desired output and prediction to be counted as error
protected int	maxEpochs max number of passes through the training set
protected int	outputSize
protected boolean	useComplementCoding
protected double	vigilanceArtA
protected double	vigilanceArtB

Constructor Summary

FuzzyArtMap()

Method Summary

protected Pattern	bThenAActivation(Pattern input, Pattern output) Activates ARTb before ARTa, this kind of activation avoids the ``match tracking anomaly'' reported in
Pattern	deScaleZeroOneOutput(Pattern pat)
OptimizationAdapter	getAdapterInstance()
double	getAlphaArtA()
double	getAlphaArtB()
double	getBetaArtA()
double	getBetaArtB()
double	getEpsilon()
int	getInputSize()
double	getMatchError()
int	getMaxEpochs()
java.lang.String	getNeuralNetworkName() Returns a human readable
int	getNumberOfArtACategories()
int	getNumberOfArtBCategories()
int	getNumberOfMismatches()
int	getOutputSize()
double	getVigilanceArtA()
double	getVigilanceArtB()
protected void	increaseSize()
protected void	init()
boolean	isUseComplementCoding()
void	oneLearningStep(Pattern input, Pattern output) Performs one learning iteration.
Pattern	predict(Pattern input) Computes a network prediction
java.util.Vector	propagate(double[][] inData)
Pattern	scaleZeroOneInput(Pattern pat)
protected InputOutputPattern[]	scaleZeroOneTrainingDataSet(InputOutputPattern[] iops)
void	setAlphaArtA(double alphaArtA)
void	setAlphaArtB(double alphaArtB)
void	setBaseArtAVigilance(double value)
void	setBetaArtA(double betaArtA)
void	setBetaArtB(double betaArtB)
void	setEpsilon(double epsilon)
void	setMatchError(double matchError)
void	setMaxEpochs(int maxEpochs)
void	setNumberOfMismatches(int numberOfMismatches)
void	setup(NeuralNetworkConfig config)
void	setUseComplementCoding(boolean useComplementCoding)
void	setVigilanceArtA(double vigilanceArtA)
void	setVigilanceArtB(double vigilanceArtB)
void	setVigilanceB(double value)
double[]	testPattern(double[] inPattern)
void	train(InputOutputPattern[] ori) Trains the network until the stop criteria is met.
NeuralNetworkConfig	yieldConfiguration()

Methods inherited from class yawn.nn.NeuralNetwork

getAdapting, getStatisticsFacility, isAdapting, setAdapting, setStatisticsFacility

Methods inherited from class java.lang.Object

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

Field Detail

alphaArtA

protected double alphaArtA

alphaArtB

protected double alphaArtB

artA

protected FuzzyArt artA

artB

protected FuzzyArt artB

betaArtA

protected double betaArtA

betaArtB

protected double betaArtB

epsilon

protected double epsilon

small amount added when doing match tracking

inputSize

protected int inputSize

matchError

protected double matchError

max difference between desired output and prediction to be counted as error

maxEpochs

protected int maxEpochs

max number of passes through the training set

outputSize

protected int outputSize

useComplementCoding

protected boolean useComplementCoding

vigilanceArtA

protected double vigilanceArtA

vigilanceArtB

protected double vigilanceArtB

Constructor Detail

FuzzyArtMap

public FuzzyArtMap()

Method Detail

bThenAActivation

protected Pattern bThenAActivation(Pattern input,
                                   Pattern output)

Activates ARTb before ARTa, this kind of activation avoids the ``match tracking anomaly'' reported in

Bartfai, G. (1996)On the Match Tracking Anomaly of the ARTMAP Neural Network. Neural Networks, 2 (9): 295-308.

Parameters:

input - the ARTa input pattern

output - the ARTb input pattern

Returns:

network prediction

deScaleZeroOneOutput

public Pattern deScaleZeroOneOutput(Pattern pat)

getAdapterInstance

public OptimizationAdapter getAdapterInstance()

Specified by:

getAdapterInstance in interface OptimizableModel

getAlphaArtA

public double getAlphaArtA()

Returns:

Returns the alphaArtA.

getAlphaArtB

public double getAlphaArtB()

Returns:

Returns the alphaArtB.

getBetaArtA

public double getBetaArtA()

Returns:

Returns the betaArtA.

getBetaArtB

public double getBetaArtB()

Returns:

Returns the betaArtB.

getEpsilon

public double getEpsilon()

Returns:

Returns the epsilon.

getInputSize

public int getInputSize()

Specified by:

getInputSize in class NeuralNetwork

getMatchError

public double getMatchError()

Returns:

Returns the matchError.

getMaxEpochs

public int getMaxEpochs()

Returns:

Returns the maxEpochs.

getNeuralNetworkName

public java.lang.String getNeuralNetworkName()

Description copied from class: NeuralNetwork

Returns a human readable

Specified by:

getNeuralNetworkName in class NeuralNetwork

Returns:

The name

See Also:

NeuralNetwork.getNeuralNetworkName()

getNumberOfArtACategories

public int getNumberOfArtACategories()

getNumberOfArtBCategories

public int getNumberOfArtBCategories()

getNumberOfMismatches

public int getNumberOfMismatches()

Returns:

Returns the numberOfMismatches.

getOutputSize

public int getOutputSize()

Specified by:

getOutputSize in class NeuralNetwork

getVigilanceArtA

public double getVigilanceArtA()

Returns:

Returns the vigilanceArtA.

getVigilanceArtB

public double getVigilanceArtB()

Returns:

Returns the vigilanceArtB.

increaseSize

protected void increaseSize()

init

protected void init()

isUseComplementCoding

public boolean isUseComplementCoding()

Returns:

Returns the useComplementCoding.

oneLearningStep

public void oneLearningStep(Pattern input,
                            Pattern output)

Description copied from class: NeuralNetwork

Performs one learning iteration.

Specified by:

oneLearningStep in class NeuralNetwork

Parameters:

input - The network input.

output - The desired output.

predict

public Pattern predict(Pattern input)

Description copied from class: NeuralNetwork

Computes a network prediction

Specified by:

predict in class NeuralNetwork

Parameters:

input - The input to propagate.

Returns:

the network output.

propagate

public java.util.Vector propagate(double[][] inData)

scaleZeroOneInput

public Pattern scaleZeroOneInput(Pattern pat)

scaleZeroOneTrainingDataSet

protected InputOutputPattern[] scaleZeroOneTrainingDataSet(InputOutputPattern[] iops)

setAlphaArtA

public void setAlphaArtA(double alphaArtA)

Parameters:

alphaArtA - The alphaArtA to set.

setAlphaArtB

public void setAlphaArtB(double alphaArtB)

Parameters:

alphaArtB - The alphaArtB to set.

setBaseArtAVigilance

public void setBaseArtAVigilance(double value)

setBetaArtA

public void setBetaArtA(double betaArtA)

Parameters:

betaArtA - The betaArtA to set.

setBetaArtB

public void setBetaArtB(double betaArtB)

Parameters:

betaArtB - The betaArtB to set.

setEpsilon

public void setEpsilon(double epsilon)

Parameters:

epsilon - The epsilon to set.

setMatchError

public void setMatchError(double matchError)

Parameters:

matchError - The matchError to set.

setMaxEpochs

public void setMaxEpochs(int maxEpochs)

Parameters:

maxEpochs - The maxEpochs to set.

setNumberOfMismatches

public void setNumberOfMismatches(int numberOfMismatches)

Parameters:

numberOfMismatches - The numberOfMismatches to set.

setup

public void setup(NeuralNetworkConfig config)
           throws ConfigurationException

Specified by:

setup in class NeuralNetwork

Throws:

ConfigurationException

setUseComplementCoding

public void setUseComplementCoding(boolean useComplementCoding)

Parameters:

useComplementCoding - The useComplementCoding to set.

setVigilanceArtA

public void setVigilanceArtA(double vigilanceArtA)

Parameters:

vigilanceArtA - The vigilanceArtA to set.

setVigilanceArtB

public void setVigilanceArtB(double vigilanceArtB)

Parameters:

vigilanceArtB - The vigilanceArtB to set.

setVigilanceB

public void setVigilanceB(double value)

testPattern

public double[] testPattern(double[] inPattern)

train

public void train(InputOutputPattern[] ori)

Description copied from class: NeuralNetwork

Trains the network until the stop criteria is met.

Specified by:

train in class NeuralNetwork

Parameters:

ori - The training set to be learned.

yieldConfiguration

public NeuralNetworkConfig yieldConfiguration()

Specified by:

yieldConfiguration in class NeuralNetwork