weka.attributeSelection

Class RankSearch

java.lang.Object

weka.attributeSelection.ASSearch

weka.attributeSelection.RankSearch

All Implemented Interfaces:

Serializable, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class RankSearch
extends ASSearch
implements OptionHandler, TechnicalInformationHandler

RankSearch :

Uses an attribute/subset evaluator to rank all attributes. If a subset evaluator is specified, then a forward selection search is used to generate a ranked list. From the ranked list of attributes, subsets of increasing size are evaluated, ie. The best attribute, the best attribute plus the next best attribute, etc.... The best attribute set is reported. RankSearch is linear in the number of attributes if a simple attribute evaluator is used such as GainRatioAttributeEval. For more information see:

Mark Hall, Geoffrey Holmes (2003). Benchmarking attribute selection techniques for discrete class data mining. IEEE Transactions on Knowledge and Data Engineering. 15(6):1437-1447.

Valid options are:

 -A <attribute evaluator>
  class name of attribute evaluator to use for ranking. Place any
  evaluator options LAST on the command line following a "--".
  eg.:
   -A weka.attributeSelection.GainRatioAttributeEval ... -- -M
  (default: weka.attributeSelection.GainRatioAttributeEval)

 -S <step size>
  number of attributes to be added from the
  ranking in each iteration (default = 1).

 -R <start point>
  point in the ranking to start evaluating from. 
  (default = 0, ie. the head of the ranking).

 
 Options specific to evaluator weka.attributeSelection.GainRatioAttributeEval:
 

 -M
  treat missing values as a seperate value.

Version:

$Revision: 6253 $

Author:

Mark Hall ([email protected])

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
RankSearch() Constructor

Method Summary

Methods

Modifier and Type	Method and Description
String	attributeEvaluatorTipText() Returns the tip text for this property
ASEvaluation	getAttributeEvaluator() Get the attribute evaluator used to generate the ranking.
String[]	getOptions() Gets the current settings of WrapperSubsetEval.
String	getRevision() Returns the revision string.
int	getStartPoint() Get the point at which to start evaluating the ranking
int	getStepSize() Get the number of attributes to add from the rankining in each iteration
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.
String	globalInfo() Returns a string describing this search method
Enumeration	listOptions() Returns an enumeration describing the available options.
int[]	search(ASEvaluation ASEval, Instances data) Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.
void	setAttributeEvaluator(ASEvaluation newEvaluator) Set the attribute evaluator to use for generating the ranking.
void	setOptions(String[] options) Parses a given list of options.
void	setStartPoint(int sp) Set the point at which to start evaluating the ranking
void	setStepSize(int ss) Set the number of attributes to add from the rankining in each iteration
String	startPointTipText() Returns the tip text for this property
String	stepSizeTipText() Returns the tip text for this property
String	toString() returns a description of the search as a String

Methods inherited from class weka.attributeSelection.ASSearch

forName, makeCopies

Methods inherited from class java.lang.Object

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

Constructor Detail

RankSearch

public RankSearch()

Constructor

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this search method

Returns:

a description of the search method 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

attributeEvaluatorTipText

public String attributeEvaluatorTipText()

Returns the tip text for this property

Returns:

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

setAttributeEvaluator

public void setAttributeEvaluator(ASEvaluation newEvaluator)

Set the attribute evaluator to use for generating the ranking.

Parameters:

newEvaluator - the attribute evaluator to use.

getAttributeEvaluator

public ASEvaluation getAttributeEvaluator()

Get the attribute evaluator used to generate the ranking.

Returns:

the evaluator used to generate the ranking.

stepSizeTipText

public String stepSizeTipText()

Returns the tip text for this property

Returns:

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

setStepSize

public void setStepSize(int ss)

Set the number of attributes to add from the rankining in each iteration

Parameters:

ss - the number of attribes to add.

getStepSize

public int getStepSize()

Get the number of attributes to add from the rankining in each iteration

Returns:

the number of attributes to add.

startPointTipText

public String startPointTipText()

Returns the tip text for this property

Returns:

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

setStartPoint

public void setStartPoint(int sp)

Set the point at which to start evaluating the ranking

Parameters:

sp - the position in the ranking to start at

getStartPoint

public int getStartPoint()

Get the point at which to start evaluating the ranking

Returns:

the position in the ranking to start at

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:

 -A <attribute evaluator>
  class name of attribute evaluator to use for ranking. Place any
  evaluator options LAST on the command line following a "--".
  eg.:
   -A weka.attributeSelection.GainRatioAttributeEval ... -- -M
  (default: weka.attributeSelection.GainRatioAttributeEval)

 -S <step size>
  number of attributes to be added from the
  ranking in each iteration (default = 1).

 -R <start point>
  point in the ranking to start evaluating from. 
  (default = 0, ie. the head of the ranking).

 
 Options specific to evaluator weka.attributeSelection.GainRatioAttributeEval:
 

 -M
  treat missing values as a seperate value.

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

getOptions

public String[] getOptions()

Gets the current settings of WrapperSubsetEval.

Specified by:

getOptions in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions()

search

public int[] search(ASEvaluation ASEval,
           Instances data)
             throws Exception

Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.

Specified by:

search in class ASSearch

Parameters:

ASEval - the subset evaluator to guide the search

data - the training instances.

Returns:

an array (not necessarily ordered) of selected attribute indexes

Throws:

Exception - if the search can't be completed

toString

public String toString()

returns a description of the search as a String

Overrides:

toString in class Object

Returns:

a description of the search

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class ASSearch

Returns:

the revision