org.encog.neural.cpn
Class CPN

java.lang.Object
  org.encog.ml.BasicML
      org.encog.neural.cpn.CPN

All Implemented Interfaces:

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

public class CPN
extends BasicML
implements MLRegression, MLResettable, MLError

Counterpropagation Neural Networks (CPN) were developed by Professor Robert Hecht-Nielsen in 1987. CPN neural networks are a hybrid neural network, employing characteristics of both a feedforward neural network and a self-organzing map (SOM). The CPN is composed of three layers, the input, the instar and the outstar. The connection from the input to the instar layer is competitive, with only one neuron being allowed to win. The connection between the instar and outstar is feedforward. The layers are trained separately, using instar training and outstar training. The CPN network is good at regression.

See Also:

Serialized Form

Constructor Summary

CPN(int theInputCount, int theInstarCount, int theOutstarCount, int theWinnerCount)
Construct the counterpropagation neural network.

Method Summary

double	calculateError(MLDataSet data) Calculate the error for this neural network.
MLData	compute(MLData input) Compute regression.
MLData	computeInstar(MLData input) Compute the instar layer.
MLData	computeOutstar(MLData input) Compute the outstar layer.
int	getInputCount()
int	getInstarCount()
int	getOutputCount()
int	getOutstarCount()
Matrix	getWeightsInputToInstar()
Matrix	getWeightsInstarToOutstar()
int	getWinnerCount()
void	reset() Reset the weights.
void	reset(int seed) Reset the weights with a seed.
void	updateProperties() Update any objeccts when a property changes.

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

Constructor Detail

CPN

public CPN(int theInputCount,
           int theInstarCount,
           int theOutstarCount,
           int theWinnerCount)

Construct the counterpropagation neural network.

Parameters:

theInputCount - The number of input neurons.

theInstarCount - The number of instar neurons.

theOutstarCount - The number of outstar neurons.

theWinnerCount - The winner count.

Method Detail

calculateError

public final double calculateError(MLDataSet data)

Calculate the error for this neural network.

Specified by:

calculateError in interface MLError

Parameters:

data - The training set.

Returns:

The error percentage.

compute

public final MLData compute(MLData input)

Compute regression.

Specified by:

compute in interface MLRegression

Parameters:

input - The input data.

Returns:

The output data.

computeInstar

public final MLData computeInstar(MLData input)

Compute the instar layer.

Parameters:

input - The input.

Returns:

The output.

computeOutstar

public final MLData computeOutstar(MLData input)

Compute the outstar layer.

Parameters:

input - The input.

Returns:

The output.

getInputCount

public final int getInputCount()

Specified by:

getInputCount in interface MLInput

Returns:

The input.

getInstarCount

public final int getInstarCount()

Returns:

The instar count, same as the input count.

getOutputCount

public final int getOutputCount()

Specified by:

getOutputCount in interface MLOutput

Returns:

The output count.

getOutstarCount

public final int getOutstarCount()

Returns:

The outstar count, same as the output count.

getWeightsInputToInstar

public final Matrix getWeightsInputToInstar()

Returns:

The weights between the input and instar.

getWeightsInstarToOutstar

public final Matrix getWeightsInstarToOutstar()

Returns:

The weights between the instar and outstar.

getWinnerCount

public final int getWinnerCount()

Returns:

The winner count.

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.

updateProperties

public void updateProperties()

Update any objeccts when a property changes.

Specified by:

updateProperties in interface MLProperties

Specified by:

updateProperties in class BasicML