weka.attributeSelection
Class ReliefFAttributeEval

java.lang.Object
  |
  +--weka.attributeSelection.ASEvaluation
        |
        +--weka.attributeSelection.AttributeEvaluator
              |
              +--weka.attributeSelection.ReliefFAttributeEval

All Implemented Interfaces:

OptionHandler, java.io.Serializable

public class ReliefFAttributeEval

extends AttributeEvaluator

implements OptionHandler

Class for Evaluating attributes individually using ReliefF.

For more information see:

Kira, K. and Rendell, L. A. (1992). A practical approach to feature selection. In D. Sleeman and P. Edwards, editors, Proceedings of the International Conference on Machine Learning, pages 249-256. Morgan Kaufmann.

Kononenko, I. (1994). Estimating attributes: analysis and extensions of Relief. In De Raedt, L. and Bergadano, F., editors, Machine Learning: ECML-94, pages 171-182. Springer Verlag.

Marko Robnik Sikonja, Igor Kononenko: An adaptation of Relief for attribute estimation on regression. In D.Fisher (ed.): Machine Learning, Proceedings of 14th International Conference on Machine Learning ICML'97, Nashville, TN, 1997.

Valid options are: -M
Specify the number of instances to sample when estimating attributes.
If not specified then all instances will be used.

-D
Seed for randomly sampling instances.

-K
Number of nearest neighbours to use for estimating attributes.
(Default is 10).

-W
Weight nearest neighbours by distance.

-A
Specify sigma value (used in an exp function to control how quickly
weights decrease for more distant instances). Use in conjunction with
-W. Sensible values = 1/5 to 1/10 the number of nearest neighbours.

Version:

$Revision: 1.15 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

ReliefFAttributeEval()
Constructor

Method Summary

void	buildEvaluator(Instances data) Initializes a ReliefF attribute evaluator.
double	evaluateAttribute(int attribute) Evaluates an individual attribute using ReliefF's instance based approach.
int	getNumNeighbours() Get the number of nearest neighbours
java.lang.String[]	getOptions() Gets the current settings of ReliefFAttributeEval.
int	getSampleSize() Get the number of instances used for estimating attributes
int	getSeed() Get the seed used for randomly sampling instances.
int	getSigma() Get the value of sigma.
boolean	getWeightByDistance() Get whether nearest neighbours are being weighted by distance
java.lang.String	globalInfo() Returns a string describing this attribute evaluator
java.util.Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(java.lang.String[] args) Main method for testing this class.
java.lang.String	numNeighboursTipText() Returns the tip text for this property
java.lang.String	sampleSizeTipText() Returns the tip text for this property
java.lang.String	seedTipText() Returns the tip text for this property
void	setNumNeighbours(int n) Set the number of nearest neighbours
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setSampleSize(int s) Set the number of instances to sample for attribute estimation
void	setSeed(int s) Set the random number seed for randomly sampling instances.
void	setSigma(int s) Sets the sigma value.
void	setWeightByDistance(boolean b) Set the nearest neighbour weighting method
java.lang.String	sigmaTipText() Returns the tip text for this property
java.lang.String	toString() Return a description of the ReliefF attribute evaluator.
java.lang.String	weightByDistanceTipText() Returns the tip text for this property

Methods inherited from class weka.attributeSelection.ASEvaluation

forName, makeCopies, postProcess

Methods inherited from class java.lang.Object

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

Constructor Detail

ReliefFAttributeEval

public ReliefFAttributeEval()

Constructor

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this attribute evaluator

Returns:

a description of the evaluator suitable for displaying in the explorer/experimenter gui

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options. Valid options are:

-M
Specify the number of instances to sample when estimating attributes.
If not specified then all instances will be used.

-D
Seed for randomly sampling instances.

-K
Number of nearest neighbours to use for estimating attributes.
(Default is 10).

-W
Weight nearest neighbours by distance.

-A
Specify sigma value (used in an exp function to control how quickly
weights decrease for more distant instances). Use in conjunction with
-W. Sensible values = 1/5 to 1/10 the number of nearest neighbours.

Specified by:

setOptions in interface OptionHandler

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

sigmaTipText

public java.lang.String sigmaTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setSigma

public void setSigma(int s)
              throws java.lang.Exception

Sets the sigma value.

Parameters:

s - the value of sigma (> 0)

Throws:

java.lang.Exception - if s is not positive

getSigma

public int getSigma()

Get the value of sigma.

Returns:

the sigma value.

numNeighboursTipText

public java.lang.String numNeighboursTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setNumNeighbours

public void setNumNeighbours(int n)

Set the number of nearest neighbours

Parameters:

n - the number of nearest neighbours.

getNumNeighbours

public int getNumNeighbours()

Get the number of nearest neighbours

Returns:

the number of nearest neighbours

seedTipText

public java.lang.String seedTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setSeed

public void setSeed(int s)

Set the random number seed for randomly sampling instances.

Parameters:

s - the random number seed.

getSeed

public int getSeed()

Get the seed used for randomly sampling instances.

Returns:

the random number seed.

sampleSizeTipText

public java.lang.String sampleSizeTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setSampleSize

public void setSampleSize(int s)

Set the number of instances to sample for attribute estimation

Parameters:

s - the number of instances to sample.

getSampleSize

public int getSampleSize()

Get the number of instances used for estimating attributes

Returns:

the number of instances.

weightByDistanceTipText

public java.lang.String weightByDistanceTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setWeightByDistance

public void setWeightByDistance(boolean b)

Set the nearest neighbour weighting method

Parameters:

b - true nearest neighbours are to be weighted by distance.

getWeightByDistance

public boolean getWeightByDistance()

Get whether nearest neighbours are being weighted by distance

Returns:

m_weightByDiffernce

getOptions

public java.lang.String[] getOptions()

Gets the current settings of ReliefFAttributeEval.

Specified by:

getOptions in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions()

toString

public java.lang.String toString()

Return a description of the ReliefF attribute evaluator.

Overrides:

toString in class java.lang.Object

Returns:

a description of the evaluator as a String.

buildEvaluator

public void buildEvaluator(Instances data)
                    throws java.lang.Exception

Initializes a ReliefF attribute evaluator.

Specified by:

buildEvaluator in class ASEvaluation

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if the evaluator has not been generated successfully

evaluateAttribute

public double evaluateAttribute(int attribute)
                         throws java.lang.Exception

Evaluates an individual attribute using ReliefF's instance based approach. The actual work is done by buildEvaluator which evaluates all features.

Specified by:

evaluateAttribute in class AttributeEvaluator

Parameters:

attribute - the index of the attribute to be evaluated

Returns:

the "merit" of the attribute

Throws:

java.lang.Exception - if the attribute could not be evaluated

main

public static void main(java.lang.String[] args)

Main method for testing this class.

Parameters:

args - the options