weka.attributeSelection

Class AttributeSelection

java.lang.Object

weka.attributeSelection.AttributeSelection

All Implemented Interfaces:

java.io.Serializable, RevisionHandler

public class AttributeSelection
extends java.lang.Object
implements java.io.Serializable, RevisionHandler

Attribute selection class. Takes the name of a search class and an evaluation class on the command line.

Valid options are:

-h
Display help.

-i <name of input file>
Specify the training data file.

-c <class index>
The index of the attribute to use as the class.

-s <search method>
The full class name of the search method followed by search method options (if any).
Eg. -s "weka.attributeSelection.BestFirst -N 10"

-x <number of folds>
Perform a cross validation.

-n <random number seed>
Specify a random number seed. Use in conjuction with -x. (Default = 1).

------------------------------------------------------------------------

Example usage as the main of an attribute evaluator (called FunkyEvaluator):

 public static void main(String[] args) {
   runEvaluator(new FunkyEvaluator(), args);
 }
 

------------------------------------------------------------------------

Version:

$Revision: 11942 $

Author:

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AttributeSelection() constructor.

Method Summary

Modifier and Type	Method and Description
java.lang.String	CrossValidateAttributes() Perform a cross validation for attribute selection.
java.lang.String	CVResultsString() returns a string summarizing the results of repeated attribute selection runs on splits of a dataset.
java.lang.String	getRevision() Returns the revision string.
static void	main(java.lang.String[] args) Main method for testing this class.
int	numberAttributesSelected() Return the number of attributes selected from the most recent run of attribute selection
double[][]	rankedAttributes() get the final ranking of the attributes.
Instance	reduceDimensionality(Instance in) reduce the dimensionality of a single instance to include only those attributes chosen by the last run of attribute selection.
Instances	reduceDimensionality(Instances in) reduce the dimensionality of a set of instances to include only those attributes chosen by the last run of attribute selection.
static java.lang.String	SelectAttributes(ASEvaluation ASEvaluator, java.lang.String[] options) Perform attribute selection with a particular evaluator and a set of options specifying search method and input file etc.
static java.lang.String	SelectAttributes(ASEvaluation ASEvaluator, java.lang.String[] options, Instances train) Perform attribute selection with a particular evaluator and a set of options specifying search method and options for the search method and evaluator.
void	SelectAttributes(Instances data) Perform attribute selection on the supplied training instances.
void	selectAttributesCVSplit(Instances split) Select attributes for a split of the data.
int[]	selectedAttributes() get the final selected set of attributes.
void	setEvaluator(ASEvaluation evaluator) set the attribute/subset evaluator
void	setFolds(int folds) set the number of folds for cross validation
void	setRanking(boolean r) produce a ranking (if possible with the set search and evaluator)
void	setSearch(ASSearch search) set the search method
void	setSeed(int s) set the seed for use in cross validation
void	setXval(boolean x) do a cross validation
java.lang.String	toResultsString() get a description of the attribute selection
void	updateStatsForModelCVSplit(Instances split, ASEvaluation evaluator, ASSearch search, int[] attributeSet, boolean doRank) Update the attribute selection stats for a cross-validation fold of the data.

Methods inherited from class java.lang.Object

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

Constructor Detail

AttributeSelection

public AttributeSelection()

constructor. Sets defaults for each member varaible. Default attribute evaluator is CfsSubsetEval; default search method is BestFirst.

Method Detail

numberAttributesSelected

public int numberAttributesSelected()
                             throws java.lang.Exception

Return the number of attributes selected from the most recent run of attribute selection

Returns:

the number of attributes selected

Throws:

java.lang.Exception

selectedAttributes

public int[] selectedAttributes()
                         throws java.lang.Exception

get the final selected set of attributes.

Returns:

an array of attribute indexes

Throws:

java.lang.Exception - if attribute selection has not been performed yet

rankedAttributes

public double[][] rankedAttributes()
                            throws java.lang.Exception

get the final ranking of the attributes.

Returns:

a two dimensional array of ranked attribute indexes and their associated merit scores as doubles.

Throws:

java.lang.Exception - if a ranking has not been produced

setEvaluator

public void setEvaluator(ASEvaluation evaluator)

set the attribute/subset evaluator

Parameters:

evaluator - the evaluator to use

setSearch

public void setSearch(ASSearch search)

set the search method

Parameters:

search - the search method to use

setFolds

public void setFolds(int folds)

set the number of folds for cross validation

Parameters:

folds - the number of folds

setRanking

public void setRanking(boolean r)

produce a ranking (if possible with the set search and evaluator)

Parameters:

r - true if a ranking is to be produced

setXval

public void setXval(boolean x)

do a cross validation

Parameters:

x - true if a cross validation is to be performed

setSeed

public void setSeed(int s)

set the seed for use in cross validation

Parameters:

s - the seed

toResultsString

public java.lang.String toResultsString()

get a description of the attribute selection

Returns:

a String describing the results of attribute selection

reduceDimensionality

public Instances reduceDimensionality(Instances in)
                               throws java.lang.Exception

reduce the dimensionality of a set of instances to include only those attributes chosen by the last run of attribute selection.

Parameters:

in - the instances to be reduced

Returns:

a dimensionality reduced set of instances

Throws:

java.lang.Exception - if the instances can't be reduced

reduceDimensionality

public Instance reduceDimensionality(Instance in)
                              throws java.lang.Exception

reduce the dimensionality of a single instance to include only those attributes chosen by the last run of attribute selection.

Parameters:

in - the instance to be reduced

Returns:

a dimensionality reduced instance

Throws:

java.lang.Exception - if the instance can't be reduced

SelectAttributes

public static java.lang.String SelectAttributes(ASEvaluation ASEvaluator,
                                                java.lang.String[] options)
                                         throws java.lang.Exception

Perform attribute selection with a particular evaluator and a set of options specifying search method and input file etc.

Parameters:

ASEvaluator - an evaluator object

options - an array of options, not only for the evaluator but also the search method (if any) and an input data file

Returns:

the results of attribute selection as a String

Throws:

java.lang.Exception - if no training file is set

CVResultsString

public java.lang.String CVResultsString()
                                 throws java.lang.Exception

returns a string summarizing the results of repeated attribute selection runs on splits of a dataset.

Returns:

a summary of attribute selection results

Throws:

java.lang.Exception - if no attribute selection has been performed.

selectAttributesCVSplit

public void selectAttributesCVSplit(Instances split)
                             throws java.lang.Exception

Select attributes for a split of the data. Calling this function updates the statistics on attribute selection. CVResultsString() returns a string summarizing the results of repeated calls to this function. Assumes that splits are from the same dataset--- ie. have the same number and types of attributes as previous splits.

Parameters:

split - the instances to select attributes from

Throws:

java.lang.Exception - if an error occurs

updateStatsForModelCVSplit

public void updateStatsForModelCVSplit(Instances split,
                                       ASEvaluation evaluator,
                                       ASSearch search,
                                       int[] attributeSet,
                                       boolean doRank)
                                throws java.lang.Exception

Update the attribute selection stats for a cross-validation fold of the data.

Parameters:

split - the instances in this split/fold of the data

evaluator - the evaluator that was used

search - the search that was used

attributeSet - the final subset produced for the split

doRank - whether to produce a ranking

Throws:

java.lang.Exception - if a problem occurs

CrossValidateAttributes

public java.lang.String CrossValidateAttributes()
                                         throws java.lang.Exception

Perform a cross validation for attribute selection. With subset evaluators the number of times each attribute is selected over the cross validation is reported. For attribute evaluators, the average merit and average ranking + std deviation is reported for each attribute.

Returns:

the results of cross validation as a String

Throws:

java.lang.Exception - if an error occurs during cross validation

SelectAttributes

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

Perform attribute selection on the supplied training instances.

Parameters:

data - the instances to select attributes from

Throws:

java.lang.Exception - if there is a problem during selection

SelectAttributes

public static java.lang.String SelectAttributes(ASEvaluation ASEvaluator,
                                                java.lang.String[] options,
                                                Instances train)
                                         throws java.lang.Exception

Perform attribute selection with a particular evaluator and a set of options specifying search method and options for the search method and evaluator.

Parameters:

ASEvaluator - an evaluator object

options - an array of options, not only for the evaluator but also the search method (if any) and an input data file

train - the input instances

Returns:

the results of attribute selection as a String

Throws:

java.lang.Exception - if incorrect options are supplied

main

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

Main method for testing this class.

Parameters:

args - the options

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Returns:

the revision