org.encog.ensemble

Class GenericEnsembleML

java.lang.Object

org.encog.ensemble.GenericEnsembleML

All Implemented Interfaces:

EnsembleML, MLClassification, MLInput, MLInputOutput, MLMethod, MLOutput, MLRegression

public class GenericEnsembleML
extends java.lang.Object
implements EnsembleML

Constructor Summary

Constructors

Constructor and Description
GenericEnsembleML(MLMethod fromML, java.lang.String description)

Method Summary

Modifier and Type	Method and Description
int	classify(MLData input) Classify the input into a group.
MLData	compute(MLData input) Compute regression.
double	getError(EnsembleDataSet testset) Get the error for this ML on the dataset
int	getInputCount()
java.lang.String	getLabel()
MLMethod	getMl()
int	getOutputCount()
MLTrain	getTraining()
EnsembleDataSet	getTrainingSet()
void	setMl(MLMethod newMl) Set the MLMethod to run
void	setTraining(MLTrain train) Set the training for this member
void	setTrainingSet(EnsembleDataSet dataSet) Set the dataset for this member
void	train(double targetError) Train the ML to a certain accuracy.
void	train(double targetError, boolean verbose) Train the ML to a certain accuracy.
void	train(double targetError, int maxIterations) Train the ML to a certain accuracy.
void	train(double targetError, int maxIterations, boolean verbose) Train the ML to a certain accuracy.
void	trainStep()
int	winner(MLData output)

Methods inherited from class java.lang.Object

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

Constructor Detail

GenericEnsembleML

public GenericEnsembleML(MLMethod fromML,
                         java.lang.String description)

Method Detail

setTrainingSet

public void setTrainingSet(EnsembleDataSet dataSet)

Description copied from interface: EnsembleML

Set the dataset for this member

Specified by:

setTrainingSet in interface EnsembleML

Parameters:

dataSet - The data set.

getTrainingSet

public EnsembleDataSet getTrainingSet()

Specified by:

getTrainingSet in interface EnsembleML

Returns:

Get the dataset for this member

train

public void train(double targetError,
                  int maxIterations,
                  boolean verbose)

Description copied from interface: EnsembleML

Train the ML to a certain accuracy.

Specified by:

train in interface EnsembleML

Parameters:

targetError - Target error.

maxIterations - Stop after this number of iterations

verbose - Verbose mode.

train

public void train(double targetError)

Description copied from interface: EnsembleML

Train the ML to a certain accuracy.

Specified by:

train in interface EnsembleML

Parameters:

targetError - The target error.

train

public void train(double targetError,
                  int maxIterations)

Description copied from interface: EnsembleML

Train the ML to a certain accuracy.

Specified by:

train in interface EnsembleML

Parameters:

targetError - Target error.

maxIterations - Stop after this number of iterations

train

public void train(double targetError,
                  boolean verbose)

Description copied from interface: EnsembleML

Train the ML to a certain accuracy.

Specified by:

train in interface EnsembleML

Parameters:

targetError - Target error.

verbose - Verbose mode.

setMl

public void setMl(MLMethod newMl)

Description copied from interface: EnsembleML

Set the MLMethod to run

Specified by:

setMl in interface EnsembleML

Parameters:

newMl - The new ML.

getMl

public MLMethod getMl()

Specified by:

getMl in interface EnsembleML

Returns:

Returns the current MLMethod

classify

public int classify(MLData input)

Description copied from interface: MLClassification

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 MLData compute(MLData input)

Description copied from interface: MLRegression

Compute regression.

Specified by:

compute in interface MLRegression

Parameters:

input - The input data.

Returns:

The output data.

getInputCount

public int getInputCount()

Specified by:

getInputCount in interface MLInput

Returns:

The input.

getOutputCount

public int getOutputCount()

Specified by:

getOutputCount in interface MLOutput

Returns:

The output count.

winner

public int winner(MLData output)

setTraining

public void setTraining(MLTrain train)

Description copied from interface: EnsembleML

Set the training for this member

Specified by:

setTraining in interface EnsembleML

Parameters:

train - The trainer.

getTraining

public MLTrain getTraining()

Specified by:

getTraining in interface EnsembleML

Returns:

Get the dataset for this member.

trainStep

public void trainStep()

Specified by:

trainStep in interface EnsembleML

getLabel

public java.lang.String getLabel()

Specified by:

getLabel in interface EnsembleML

getError

public double getError(EnsembleDataSet testset)

Description copied from interface: EnsembleML

Get the error for this ML on the dataset

Specified by:

getError in interface EnsembleML

Parameters:

testset - The dataset.

Returns:

The error.