weka.attributeSelection

Class ReliefFAttributeEval

java.lang.Object

weka.attributeSelection.ASEvaluation

weka.attributeSelection.ReliefFAttributeEval

All Implemented Interfaces:

Serializable, AttributeEvaluator, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class ReliefFAttributeEval
extends ASEvaluation
implements AttributeEvaluator, OptionHandler, TechnicalInformationHandler

ReliefFAttributeEval :

Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class. Can operate on both discrete and continuous class data.

For more information see:

Kenji Kira, Larry A. Rendell: A Practical Approach to Feature Selection. In: Ninth International Workshop on Machine Learning, 249-256, 1992.

Igor Kononenko: Estimating Attributes: Analysis and Extensions of RELIEF. In: European Conference on Machine Learning, 171-182, 1994.

Marko Robnik-Sikonja, Igor Kononenko: An adaptation of Relief for attribute estimation in regression. In: Fourteenth International Conference on Machine Learning, 296-304, 1997.

BibTeX:

 @inproceedings{Kira1992,
    author = {Kenji Kira and Larry A. Rendell},
    booktitle = {Ninth International Workshop on Machine Learning},
    editor = {Derek H. Sleeman and Peter Edwards},
    pages = {249-256},
    publisher = {Morgan Kaufmann},
    title = {A Practical Approach to Feature Selection},
    year = {1992}
 }
 
 @inproceedings{Kononenko1994,
    author = {Igor Kononenko},
    booktitle = {European Conference on Machine Learning},
    editor = {Francesco Bergadano and Luc De Raedt},
    pages = {171-182},
    publisher = {Springer},
    title = {Estimating Attributes: Analysis and Extensions of RELIEF},
    year = {1994}
 }
 
 @inproceedings{Robnik-Sikonja1997,
    author = {Marko Robnik-Sikonja and Igor Kononenko},
    booktitle = {Fourteenth International Conference on Machine Learning},
    editor = {Douglas H. Fisher},
    pages = {296-304},
    publisher = {Morgan Kaufmann},
    title = {An adaptation of Relief for attribute estimation in regression},
    year = {1997}
 }
 

Valid options are:

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

 -D <seed>
  Seed for randomly sampling instances.
  (Default = 1)

 -K <number of neighbours>
  Number of nearest neighbours (k) used
  to estimate attribute relevances
  (Default = 10).

 -W
  Weight nearest neighbours by distance

 -A <num>
  Specify sigma value (used in an exp
  function to control how quickly
  weights for more distant instances
  decrease. Use in conjunction with -W.
  Sensible value=1/5 to 1/10 of the
  number of nearest neighbours.
  (Default = 2)

Version:

$Revision: 8034 $

Author:

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ReliefFAttributeEval() Constructor

Method Summary

Methods

Modifier and Type	Method and Description
void	buildEvaluator(Instances data) Initializes a ReliefF attribute evaluator.
double	evaluateAttribute(int attribute) Evaluates an individual attribute using ReliefF's instance based approach.
Capabilities	getCapabilities() Returns the capabilities of this evaluator.
int	getNumNeighbours() Get the number of nearest neighbours
String[]	getOptions() Gets the current settings of ReliefFAttributeEval.
String	getRevision() Returns the revision string.
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.
TechnicalInformation	getTechnicalInformation() Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
boolean	getWeightByDistance() Get whether nearest neighbours are being weighted by distance
String	globalInfo() Returns a string describing this attribute evaluator
Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(String[] args) Main method for testing this class.
String	numNeighboursTipText() Returns the tip text for this property
String	sampleSizeTipText() Returns the tip text for this property
String	seedTipText() Returns the tip text for this property
void	setNumNeighbours(int n) Set the number of nearest neighbours
void	setOptions(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
String	sigmaTipText() Returns the tip text for this property
String	toString() Return a description of the ReliefF attribute evaluator.
String	weightByDistanceTipText() Returns the tip text for this property

Methods inherited from class weka.attributeSelection.ASEvaluation

forName, makeCopies, postProcess, runEvaluator

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 String globalInfo()

Returns a string describing this attribute evaluator

Returns:

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

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface TechnicalInformationHandler

Returns:

the technical information about this class

listOptions

public 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(String[] options)
                throws Exception

Parses a given list of options.

Valid options are:

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

 -D <seed>
  Seed for randomly sampling instances.
  (Default = 1)

 -K <number of neighbours>
  Number of nearest neighbours (k) used
  to estimate attribute relevances
  (Default = 10).

 -W
  Weight nearest neighbours by distance

 -A <num>
  Specify sigma value (used in an exp
  function to control how quickly
  weights for more distant instances
  decrease. Use in conjunction with -W.
  Sensible value=1/5 to 1/10 of the
  number of nearest neighbours.
  (Default = 2)

Specified by:

setOptions in interface OptionHandler

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

sigmaTipText

public 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 Exception

Sets the sigma value.

Parameters:

s - the value of sigma (> 0)

Throws:

Exception - if s is not positive

getSigma

public int getSigma()

Get the value of sigma.

Returns:

the sigma value.

numNeighboursTipText

public 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 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 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 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 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 String toString()

Return a description of the ReliefF attribute evaluator.

Overrides:

toString in class Object

Returns:

a description of the evaluator as a String.

getCapabilities

public Capabilities getCapabilities()

Returns the capabilities of this evaluator.

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class ASEvaluation

Returns:

the capabilities of this evaluator

See Also:

Capabilities

buildEvaluator

public void buildEvaluator(Instances data)
                    throws Exception

Initializes a ReliefF attribute evaluator.

Specified by:

buildEvaluator in class ASEvaluation

Parameters:

data - set of instances serving as training data

Throws:

Exception - if the evaluator has not been generated successfully

evaluateAttribute

public double evaluateAttribute(int attribute)
                         throws 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 interface AttributeEvaluator

Parameters:

attribute - the index of the attribute to be evaluated

Returns:

the "merit" of the attribute

Throws:

Exception - if the attribute could not be evaluated

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class ASEvaluation

Returns:

the revision

main

public static void main(String[] args)

Main method for testing this class.

Parameters:

args - the options