org.neuroph.core.learning
Class DataSetRow

java.lang.Object
  org.neuroph.core.learning.DataSetRow

All Implemented Interfaces:

Serializable

public class DataSetRow
extends Object
implements Serializable

Represents training element for supervised learning algorithms. Each supervised training element contains network input and desired network output.

Author:

Zoran Sevarac

See Also:

Serialized Form

Field Summary

protected double[]	input Input vector for this training element
protected String	label Label for this training element

Constructor Summary

DataSetRow(ArrayList<Double> input)

DataSetRow(ArrayList<Double> input, ArrayList<Double> desiredOutput)
Creates new training element with specified input and desired output vectors

DataSetRow(double... input)
Creates new training element with input array

DataSetRow(double[] input, double[] desiredOutput)
Creates new training element with specified input and desired output vectors

DataSetRow(String input, String desiredOutput)
Creates new training element with specified input and desired output vectors specifed as strings

Method Summary

double[]	getDesiredOutput()
double[]	getInput() Returns input vector
String	getLabel() Get training element label
boolean	isSupervised()
void	setDesiredOutput(double[] desiredOutput)
void	setInput(double[] input) Sets input vector
void	setLabel(String label) Set training element label

Methods inherited from class java.lang.Object

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

Field Detail

input

protected double[] input

Input vector for this training element

label

protected String label

Label for this training element

Constructor Detail

DataSetRow

public DataSetRow(String input,
                  String desiredOutput)

Creates new training element with specified input and desired output vectors specifed as strings

Parameters:

input - input vector as space separated string

desiredOutput - desired output vector as space separated string

DataSetRow

public DataSetRow(double[] input,
                  double[] desiredOutput)

Creates new training element with specified input and desired output vectors

Parameters:

input - input array

desiredOutput - desired output array

DataSetRow

public DataSetRow(double... input)

Creates new training element with input array

Parameters:

input - input array

DataSetRow

public DataSetRow(ArrayList<Double> input,
                  ArrayList<Double> desiredOutput)

Creates new training element with specified input and desired output vectors

Parameters:

input - input vector

desiredOutput - desired output vector

DataSetRow

public DataSetRow(ArrayList<Double> input)

Method Detail

getInput

public double[] getInput()

Returns input vector

Returns:

input vector

setInput

public void setInput(double[] input)

Sets input vector

Parameters:

input - input vector

getDesiredOutput

public double[] getDesiredOutput()

setDesiredOutput

public void setDesiredOutput(double[] desiredOutput)

getLabel

public String getLabel()

Get training element label

Returns:

training element label

setLabel

public void setLabel(String label)

Set training element label

Parameters:

label - label for this training element

isSupervised

public boolean isSupervised()