OneRAttributeEval

java.lang.Object
- weka.attributeSelection.ASEvaluation
- - weka.attributeSelection.OneRAttributeEval

All Implemented Interfaces:: java.io.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: 11219 $
Author:: Mark Hall (mhall@cs.waikato.ac.nz)
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

OneRAttributeEval()
Constructor

Constructors
Constructor and Description
`OneRAttributeEval()` Constructor

Method Summary

All Methods Static Methods Instance Methods Concrete 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.
`java.lang.String`	`evalUsingTrainingDataTipText()` Returns a string for this option suitable for display in the gui as a tip text
`java.lang.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
`java.lang.String[]`	`getOptions()` returns the current setup.
`java.lang.String`	`getRevision()` Returns the revision string.
`int`	`getSeed()` Get the random number seed
`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`	`minimumBucketSizeTipText()` Returns a string for this option suitable for display in the gui as a tip text
`int[]`	`postProcess(int[] attributeSet)` Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.
`java.lang.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(java.lang.String[] options)` Parses a given list of options.
`void`	`setSeed(int seed)` Set the random number seed for cross validation
`java.lang.String`	`toString()` Return a description of the evaluator

Methods inherited from class weka.attributeSelection.ASEvaluation
clean, forName, makeCopies

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 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
  - seedTipText
```
public java.lang.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 java.lang.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 java.lang.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 java.lang.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 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:
```
 -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:
    
    java.lang.Exception - if an option is not supported
  - getOptions
```
public java.lang.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 java.lang.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:
    
    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 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:
    
    java.lang.Exception - if the attribute could not be evaluated
  - toString
```
public java.lang.String toString()
```
    Return a description of the evaluator
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    description as a string
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class ASEvaluation
    
    Returns:
    
    the revision
  - postProcess
```
public int[] postProcess(int[] attributeSet)
```
    Description copied from class: ASEvaluation
    
    Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.
    
    Overrides:
    
    postProcess in class ASEvaluation
    
    Parameters:
    
    attributeSet - the set of attributes found by the search
    
    Returns:
    
    a possibly ranked list of postprocessed attributes
  - main
```
public static void main(java.lang.String[] args)
```
    Main method for testing this class.
    
    Parameters:
    
    args - the options

Class OneRAttributeEval

Constructor Summary

Method Summary

Methods inherited from class weka.attributeSelection.ASEvaluation

Methods inherited from class java.lang.Object

Constructor Detail

OneRAttributeEval

Method Detail

globalInfo

seedTipText

setSeed

getSeed

foldsTipText

setFolds

getFolds

evalUsingTrainingDataTipText

setEvalUsingTrainingData

minimumBucketSizeTipText

setMinimumBucketSize

getMinimumBucketSize

getEvalUsingTrainingData

listOptions

setOptions

getOptions

getCapabilities

buildEvaluator

evaluateAttribute

toString

getRevision

postProcess

main