weka.attributeSelection

Class OneRAttributeEval

java.lang.Object

weka.attributeSelection.ASEvaluation

weka.attributeSelection.OneRAttributeEval

All Implemented Interfaces:

Serializable, AttributeEvaluator, CapabilitiesHandler, OptionHandler, RevisionHandler

public class OneRAttributeEval
extends ASEvaluation
implements AttributeEvaluator, OptionHandler

OneRAttributeEval :

Evaluates the worth of an attribute by using the OneR classifier.

Valid options are:

 -S <seed>
  Random number seed for cross validation
  (default = 1)

 -F <folds>
  Number of folds for cross validation
  (default = 10)

 -D
  Use training data for evaluation rather than cross validaton

 -B <minimum bucket size>
  Minimum number of objects in a bucket
  (passed on to OneR, default = 6)

Version:

$Revision: 8034 $

Author:

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
OneRAttributeEval() Constructor

Method Summary

Methods

Modifier and Type	Method and Description
void	buildEvaluator(Instances data) Initializes a OneRAttribute attribute evaluator.
double	evaluateAttribute(int attribute) evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
String	evalUsingTrainingDataTipText() Returns a string for this option suitable for display in the gui as a tip text
String	foldsTipText() Returns a string for this option suitable for display in the gui as a tip text
Capabilities	getCapabilities() Returns the capabilities of this evaluator.
boolean	getEvalUsingTrainingData() Returns true if the training data is to be used for evaluation
int	getFolds() Get the number of folds used for cross validation
int	getMinimumBucketSize() Get the minimum bucket size used by oneR
String[]	getOptions() returns the current setup.
String	getRevision() Returns the revision string.
int	getSeed() Get the random number seed
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	minimumBucketSizeTipText() Returns a string for this option suitable for display in the gui as a tip text
String	seedTipText() Returns a string for this option suitable for display in the gui as a tip text
void	setEvalUsingTrainingData(boolean e) Use the training data to evaluate attributes rather than cross validation
void	setFolds(int folds) Set the number of folds to use for cross validation
void	setMinimumBucketSize(int minB) Set the minumum bucket size used by OneR
void	setOptions(String[] options) Parses a given list of options.
void	setSeed(int seed) Set the random number seed for cross validation
String	toString() Return a description of the evaluator

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

OneRAttributeEval

public OneRAttributeEval()

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

seedTipText

public String seedTipText()

Returns a string for this option suitable for display in the gui as a tip text

Returns:

a string describing this option

setSeed

public void setSeed(int seed)

Set the random number seed for cross validation

Parameters:

seed - the seed to use

getSeed

public int getSeed()

Get the random number seed

Returns:

an int value

foldsTipText

public String foldsTipText()

Returns a string for this option suitable for display in the gui as a tip text

Returns:

a string describing this option

setFolds

public void setFolds(int folds)

Set the number of folds to use for cross validation

Parameters:

folds - the number of folds

getFolds

public int getFolds()

Get the number of folds used for cross validation

Returns:

the number of folds

evalUsingTrainingDataTipText

public String evalUsingTrainingDataTipText()

Returns a string for this option suitable for display in the gui as a tip text

Returns:

a string describing this option

setEvalUsingTrainingData

public void setEvalUsingTrainingData(boolean e)

Use the training data to evaluate attributes rather than cross validation

Parameters:

e - true if training data is to be used for evaluation

minimumBucketSizeTipText

public String minimumBucketSizeTipText()

Returns a string for this option suitable for display in the gui as a tip text

Returns:

a string describing this option

setMinimumBucketSize

public void setMinimumBucketSize(int minB)

Set the minumum bucket size used by OneR

Parameters:

minB - the minimum bucket size to use

getMinimumBucketSize

public int getMinimumBucketSize()

Get the minimum bucket size used by oneR

Returns:

the minimum bucket size used

getEvalUsingTrainingData

public boolean getEvalUsingTrainingData()

Returns true if the training data is to be used for evaluation

Returns:

true if training data is to be used for evaluation

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:

 -S <seed>
  Random number seed for cross validation
  (default = 1)

 -F <folds>
  Number of folds for cross validation
  (default = 10)

 -D
  Use training data for evaluation rather than cross validaton

 -B <minimum bucket size>
  Minimum number of objects in a bucket
  (passed on to OneR, default = 6)

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()

returns the current setup.

Specified by:

getOptions in interface OptionHandler

Returns:

the options of the current setup

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 OneRAttribute attribute evaluator. Discretizes all attributes that are numeric.

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 by measuring the amount of information gained about the class given the attribute.

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

toString

public String toString()

Return a description of the evaluator

Overrides:

toString in class Object

Returns:

description as a string

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