Package weka.attributeSelection

Class OneRAttributeEval

    • 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<Option> 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

      • 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

      • 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​(java.lang.String[] args)
        Main method for testing this class.
        Parameters:
        args - the options