weka.classifiers.lazy.kstar
Class KStarNumericAttribute

java.lang.Object
  |
  +--weka.classifiers.lazy.kstar.KStarNumericAttribute

All Implemented Interfaces:

KStarConstants

public class KStarNumericAttribute

extends java.lang.Object

implements KStarConstants

A custom class which provides the environment for computing the transformation probability of a specified test instance numeric attribute to a specified train instance numeric attribute.

Version:

$Revision 1.0 $

Author:

Len Trigg (len@reeltwo.com), Abdelaziz Mahoui (am14@cs.waikato.ac.nz)

Field Summary

Fields inherited from interface weka.classifiers.lazy.kstar.KStarConstants

B_ENTROPY, B_SPHERE, EPSILON, FLOOR, FLOOR1, INITIAL_STEP, LOG2, M_AVERAGE, M_DELETE, M_MAXDIFF, M_NORMAL, NUM_RAND_COLS, OFF, ON, ROOT_FINDER_ACCURACY, ROOT_FINDER_MAX_ITER

Constructor Summary

KStarNumericAttribute(Instance test, Instance train, int attrIndex, Instances trainSet, int[][] randClassCols, KStarCache cache)
Constructor

Method Summary

void	setBlendFactor(int factor) Set the blending factor
void	setBlendMethod(int method) Set the blending method
void	setMissingMode(int mode) Set the missing value mode.
void	setOptions(int missingmode, int blendmethod, int blendfactor) Set options.
double	transProb() Calculates the transformation probability of the attribute indexed "m_AttrIndex" in test instance "m_Test" to the same attribute in the train instance "m_Train".

Methods inherited from class java.lang.Object

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

Constructor Detail

KStarNumericAttribute

public KStarNumericAttribute(Instance test,
                             Instance train,
                             int attrIndex,
                             Instances trainSet,
                             int[][] randClassCols,
                             KStarCache cache)

Constructor

Method Detail

transProb

public double transProb()

Calculates the transformation probability of the attribute indexed "m_AttrIndex" in test instance "m_Test" to the same attribute in the train instance "m_Train".

Returns:

the probability value

setOptions

public void setOptions(int missingmode,
                       int blendmethod,
                       int blendfactor)

Set options.

Parameters:

missingmode - the missing value treatment to use

blendmethod - the blending method to use

blendfactor - the level of blending to use

setMissingMode

public void setMissingMode(int mode)

Set the missing value mode.

Parameters:

mode - the type of missing value treatment to use

setBlendMethod

public void setBlendMethod(int method)

Set the blending method

Parameters:

method - the blending method to use

setBlendFactor

public void setBlendFactor(int factor)

Set the blending factor

Parameters:

factor - the level of blending to use