keel.Algorithms.RST_Learning.EFS_RPS

Class ISW

java.lang.Object

keel.Algorithms.RST_Learning.EFS_RPS.ISW

public class ISW
extends java.lang.Object

File: ISW.java A implementation of a rough set based Instance Selection Wrapper class for EFS_RPS.

Since:

JDK1.5

Version:

1.0

Author:

Written by Joaquín Derrac (University of Granada) 13/11/2011

Field Summary

Fields

Modifier and Type	Field and Description
static int	KLEENE_DIENES
static int	LUKASIEWICZ
static int	MIN
static int	PRODUCT

Constructor Summary

Constructors

Constructor and Description
ISW()

Method Summary

Modifier and Type	Method and Description
static void	clearAttributes()
static void	clearInstances()
static double	computeISW()
static int[]	getAttributes()
static int[]	getInstances()
static int	getnFeatures()
static int	getnInstances()
static boolean	isAttribute(int att)
static void	setAllAttributes()
static void	setAllInstances()
static void	setAttribute(int att)
static void	setAttributes(int[] atts)
static void	setData(double[][] newData, boolean[] vecNominal) Loads the training data into the classifier
static void	setImplicator(int val)
static void	setInstances(int[] ins)
static void	setOutput(int[] newOutput) Loads the training output into the classifier
static void	setTNorm(int val)
static void	unsetAttribute(int att)

Methods inherited from class java.lang.Object

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

Field Detail

LUKASIEWICZ

public static final int LUKASIEWICZ

See Also:

Constant Field Values

KLEENE_DIENES

public static final int KLEENE_DIENES

See Also:

Constant Field Values

MIN

public static final int MIN

See Also:

Constant Field Values

PRODUCT

public static final int PRODUCT

See Also:

Constant Field Values

Constructor Detail

ISW

public ISW()

Method Detail

setImplicator

public static void setImplicator(int val)

setTNorm

public static void setTNorm(int val)

setData

public static void setData(double[][] newData,
                           boolean[] vecNominal)

Loads the training data into the classifier

Parameters:

newData - Data represented with continuous values

vecNominal - vector indicating which attribute is nominal or not.

setOutput

public static void setOutput(int[] newOutput)

Loads the training output into the classifier

Parameters:

newOutput - Output attribute of the training data

isAttribute

public static boolean isAttribute(int att)

setAttribute

public static void setAttribute(int att)

unsetAttribute

public static void unsetAttribute(int att)

setAttributes

public static void setAttributes(int[] atts)

setInstances

public static void setInstances(int[] ins)

getAttributes

public static int[] getAttributes()

getInstances

public static int[] getInstances()

clearAttributes

public static void clearAttributes()

clearInstances

public static void clearInstances()

getnFeatures

public static int getnFeatures()

getnInstances

public static int getnInstances()

setAllInstances

public static void setAllInstances()

setAllAttributes

public static void setAllAttributes()

computeISW

public static double computeISW()