org.encog.neural.som
Class SOM

java.lang.Object
  org.encog.ml.BasicML
      org.encog.neural.som.SOM

All Implemented Interfaces:

Serializable, MLClassification, MLError, MLInput, MLInputOutput, MLMethod, MLOutput, MLProperties, MLResettable

public class SOM
extends BasicML
implements MLClassification, MLResettable, MLError

A self organizing map neural network.

See Also:

Serialized Form

Field Summary

protected int	inputNeuronCount Number of input neurons.
protected int	outputNeuronCount Number of output neurons.
static double	VERYSMALL Do not allow patterns to go below this very small number.

Constructor Summary

SOM()
Default constructor.

SOM(int inputCount, int outputCount)
The constructor.

Method Summary

double	calculateError(MLDataSet data) Calculate the error of the ML method, given a dataset.
int	classify(MLData input) Classify the input into a group.
MLData	compute(MLData input) Determine the winner for the specified input.
int	getInputCount()
int	getInputNeuronCount() Get the input neuron count.
int	getOutputCount()
int	getOutputNeuronCount() Get the output neuron count.
Matrix	getWeights()
void	reset() Reset the weights.
void	reset(int seed) Reset the weights with a seed.
void	setInputCount(int i) Set the input count.
void	setOutputNeuronCount(int i) Set the output count.
void	setWeights(Matrix weights)
void	updateProperties() Update any objeccts when a property changes.
int	winner(MLData input) Determine the winner for the specified input.

Methods inherited from class org.encog.ml.BasicML

getProperties, getPropertyDouble, getPropertyLong, getPropertyString, setProperty, setProperty, setProperty

Methods inherited from class java.lang.Object

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

Field Detail

VERYSMALL

public static final double VERYSMALL

Do not allow patterns to go below this very small number.

See Also:

Constant Field Values

inputNeuronCount

protected int inputNeuronCount

Number of input neurons.

outputNeuronCount

protected int outputNeuronCount

Number of output neurons.

Constructor Detail

SOM

public SOM()

Default constructor.

SOM

public SOM(int inputCount,
           int outputCount)

The constructor.

Parameters:

inputCount - Number of input neurons

outputCount - Number of output neurons

Method Detail

calculateError

public final double calculateError(MLDataSet data)

Calculate the error of the ML method, given a dataset.

Specified by:

calculateError in interface MLError

Parameters:

data - The dataset.

Returns:

The error.

classify

public final int classify(MLData input)

Classify the input into a group.

Specified by:

classify in interface MLClassification

Parameters:

input - The input data to classify.

Returns:

The group that the data was classified into.

compute

public final MLData compute(MLData input)

Determine the winner for the specified input. This is the number of the winning neuron.

Parameters:

input - The input pattern.

Returns:

The winning neuron.

getInputCount

public final int getInputCount()

Specified by:

getInputCount in interface MLInput

Returns:

The input.

getInputNeuronCount

public final int getInputNeuronCount()

Get the input neuron count.

Returns:

The input neuron count.

getOutputCount

public final int getOutputCount()

Specified by:

getOutputCount in interface MLOutput

Returns:

The output count.

getOutputNeuronCount

public final int getOutputNeuronCount()

Get the output neuron count.

Returns:

The output neuron count.

getWeights

public final Matrix getWeights()

Returns:

the weights

reset

public final void reset()

Reset the weights.

Specified by:

reset in interface MLResettable

reset

public final void reset(int seed)

Reset the weights with a seed.

Specified by:

reset in interface MLResettable

Parameters:

seed - The seed value.

setInputCount

public final void setInputCount(int i)

Set the input count.

Parameters:

i - The input count.

setOutputNeuronCount

public final void setOutputNeuronCount(int i)

Set the output count.

Parameters:

i - The output count.

setWeights

public final void setWeights(Matrix weights)

Parameters:

weights - the weights to set

updateProperties

public final void updateProperties()

Update any objeccts when a property changes.

Specified by:

updateProperties in interface MLProperties

Specified by:

updateProperties in class BasicML

winner

public final int winner(MLData input)

Determine the winner for the specified input. This is the number of the winning neuron.

Parameters:

input - The input pattern.

Returns:

The winning neuron.