org.encog.ml.data.basic

Class BasicMLDataPair

java.lang.Object

org.encog.ml.data.basic.BasicMLDataPair

All Implemented Interfaces:

Serializable, MLDataPair, CentroidFactory<MLDataPair>

Direct Known Subclasses:

BasicNeuralDataPair

public class BasicMLDataPair
extends Object
implements MLDataPair, Serializable

A basic implementation of the MLDataPair interface. This implementation simply holds and input and ideal MLData object. For supervised training both input and ideal should be specified. For unsupervised training the input property should be valid, however the ideal property should contain null.

Author:

jheaton

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
BasicMLDataPair(MLData theInput) Construct the object with only input.
BasicMLDataPair(MLData theInput, MLData theIdeal) Construct a BasicMLDataPair class with the specified input and ideal values.

Method Summary

Methods

Modifier and Type	Method and Description
Centroid<MLDataPair>	createCentroid()
static MLDataPair	createPair(int inputSize, int idealSize) Create a new data pair object of the correct size for the machine learning method that is being trained.
MLData	getIdeal()
double[]	getIdealArray()
MLData	getInput()
double[]	getInputArray()
double	getSignificance() Get the significance, 1.0 is neutral.
boolean	isSupervised()
void	setIdealArray(double[] data) Set the ideal data, the desired output.
void	setInputArray(double[] data) Set the input.
void	setSignificance(double significance) Set the significance, 1.0 is neutral.
String	toString()

Methods inherited from class java.lang.Object

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

Constructor Detail

BasicMLDataPair

public BasicMLDataPair(MLData theInput)

Construct the object with only input. If this constructor is used, then unsupervised training is being used.

Parameters:

theInput - The input to the machine learning method.

BasicMLDataPair

public BasicMLDataPair(MLData theInput,
               MLData theIdeal)

Construct a BasicMLDataPair class with the specified input and ideal values.

Parameters:

theInput - The input to the machine learning method.

theIdeal - The expected results from the machine learning method.

Method Detail

createPair

public static MLDataPair createPair(int inputSize,
                    int idealSize)

Create a new data pair object of the correct size for the machine learning method that is being trained. This object will be passed to the getPair method to allow the data pair objects to be copied to it.

Parameters:

inputSize - The size of the input data.

idealSize - The size of the ideal data.

Returns:

A new data pair object.

getIdeal

public MLData getIdeal()

Specified by:

getIdeal in interface MLDataPair

Returns:

The ideal data that the neural network should produce for the specified input.

getIdealArray

public double[] getIdealArray()

Specified by:

getIdealArray in interface MLDataPair

Returns:

The ideal data that the machine learning method should produce for the specified input.

getInput

public MLData getInput()

Specified by:

getInput in interface MLDataPair

Returns:

The input that the neural network

getInputArray

public double[] getInputArray()

Specified by:

getInputArray in interface MLDataPair

Returns:

The input that the neural network

isSupervised

public boolean isSupervised()

Specified by:

isSupervised in interface MLDataPair

Returns:

True if this training pair is supervised. That is, it has both input and ideal data.

setIdealArray

public void setIdealArray(double[] data)

Set the ideal data, the desired output.

Specified by:

setIdealArray in interface MLDataPair

Parameters:

data - The ideal data.

setInputArray

public void setInputArray(double[] data)

Set the input.

Specified by:

setInputArray in interface MLDataPair

Parameters:

data - The input.

toString

public String toString()

Overrides:

toString in class Object

getSignificance

public double getSignificance()

Get the significance, 1.0 is neutral.

Specified by:

getSignificance in interface MLDataPair

Returns:

The significance.

setSignificance

public void setSignificance(double significance)

Set the significance, 1.0 is neutral.

Specified by:

setSignificance in interface MLDataPair

Parameters:

significance - The significance.

createCentroid

public Centroid<MLDataPair> createCentroid()

Specified by:

createCentroid in interface CentroidFactory<MLDataPair>

Returns:

The centroid.