Package weka.attributeSelection

Class OneRAttributeEval

java.lang.Object
weka.attributeSelection.ASEvaluation
weka.attributeSelection.OneRAttributeEval
All Implemented Interfaces:
Serializable, AttributeEvaluator, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, 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: 15519 $
Author:
Mark Hall (mhall@cs.waikato.ac.nz)
See Also:

  • Constructor Details

    • OneRAttributeEval

      public OneRAttributeEval()
      Constructor

  • Method Details

    • 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<Option> listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      Overrides:
      listOptions in class ASEvaluation
      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
      Overrides:
      setOptions in class ASEvaluation
      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
      Overrides:
      getOptions in class ASEvaluation
      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:

    • 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

    • 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. Can also be used to clean up any data structures post attribute selection.
      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(String[] args)
      Main method for testing this class.
      Parameters:
      args - the options