Package weka.attributeSelection

Class ReliefFAttributeEval

  • All Implemented Interfaces:
    java.io.Serializable, AttributeEvaluator, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler
    public class ReliefFAttributeEval
extends ASEvaluation
implements AttributeEvaluator, OptionHandler, TechnicalInformationHandler
    ReliefFAttributeEval :

    Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class. Can operate on both discrete and continuous class data.

    For more information see:

    Kenji Kira, Larry A. Rendell: A Practical Approach to Feature Selection. In: Ninth International Workshop on Machine Learning, 249-256, 1992.

    Igor Kononenko: Estimating Attributes: Analysis and Extensions of RELIEF. In: European Conference on Machine Learning, 171-182, 1994.

    Marko Robnik-Sikonja, Igor Kononenko: An adaptation of Relief for attribute estimation in regression. In: Fourteenth International Conference on Machine Learning, 296-304, 1997.

    BibTeX: 

     @inproceedings{Kira1992,
    author = {Kenji Kira and Larry A. Rendell},
    booktitle = {Ninth International Workshop on Machine Learning},
    editor = {Derek H. Sleeman and Peter Edwards},
    pages = {249-256},
    publisher = {Morgan Kaufmann},
    title = {A Practical Approach to Feature Selection},
    year = {1992}
 }
 
 @inproceedings{Kononenko1994,
    author = {Igor Kononenko},
    booktitle = {European Conference on Machine Learning},
    editor = {Francesco Bergadano and Luc De Raedt},
    pages = {171-182},
    publisher = {Springer},
    title = {Estimating Attributes: Analysis and Extensions of RELIEF},
    year = {1994}
 }
 
 @inproceedings{Robnik-Sikonja1997,
    author = {Marko Robnik-Sikonja and Igor Kononenko},
    booktitle = {Fourteenth International Conference on Machine Learning},
    editor = {Douglas H. Fisher},
    pages = {296-304},
    publisher = {Morgan Kaufmann},
    title = {An adaptation of Relief for attribute estimation in regression},
    year = {1997}
 }

    Valid options are: 

     -M <num instances>
  Specify the number of instances to
  sample when estimating attributes.
  If not specified, then all instances
  will be used.
     -D <seed>
  Seed for randomly sampling instances.
  (Default = 1)
     -K <number of neighbours>
  Number of nearest neighbours (k) used
  to estimate attribute relevances
  (Default = 10).
     -W
  Weight nearest neighbours by distance
     -A <num>
  Specify sigma value (used in an exp
  function to control how quickly
  weights for more distant instances
  decrease. Use in conjunction with -W.
  Sensible value=1/5 to 1/10 of the
  number of nearest neighbours.
  (Default = 2)
    Version:
    $Revision: 11219 $
    Author:
    Mark Hall (mhall@cs.waikato.ac.nz)
    See Also:
    Serialized Form

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      void buildEvaluator​(Instances data)
      Initializes a ReliefF attribute evaluator.
      double evaluateAttribute​(int attribute)
      Evaluates an individual attribute using ReliefF's instance based approach.
      Capabilities getCapabilities()
      Returns the capabilities of this evaluator.
      int getNumNeighbours()
      Get the number of nearest neighbours
      java.lang.String[] getOptions()
      Gets the current settings of ReliefFAttributeEval.
      java.lang.String getRevision()
      Returns the revision string.
      int getSampleSize()
      Get the number of instances used for estimating attributes
      int getSeed()
      Get the seed used for randomly sampling instances.
      int getSigma()
      Get the value of sigma.
      TechnicalInformation getTechnicalInformation()
      Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
      boolean getWeightByDistance()
      Get whether nearest neighbours are being weighted by distance
      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 numNeighboursTipText()
      Returns the tip text for this property
      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 sampleSizeTipText()
      Returns the tip text for this property
      java.lang.String seedTipText()
      Returns the tip text for this property
      void setNumNeighbours​(int n)
      Set the number of nearest neighbours
      void setOptions​(java.lang.String[] options)
      Parses a given list of options.
      void setSampleSize​(int s)
      Set the number of instances to sample for attribute estimation
      void setSeed​(int s)
      Set the random number seed for randomly sampling instances.
      void setSigma​(int s)
      Sets the sigma value.
      void setWeightByDistance​(boolean b)
      Set the nearest neighbour weighting method
      java.lang.String sigmaTipText()
      Returns the tip text for this property
      java.lang.String toString()
      Return a description of the ReliefF attribute evaluator.
      java.lang.String weightByDistanceTipText()
      Returns the tip text for this property

      • Methods inherited from class java.lang.Object

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

    • Constructor Detail

      • ReliefFAttributeEval

        public ReliefFAttributeEval()
        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

      • getTechnicalInformation

        public TechnicalInformation getTechnicalInformation()
        Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
        Specified by:
        getTechnicalInformation in interface TechnicalInformationHandler
        Returns:
        the technical information about this class

      • 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: 

         -M <num instances>
  Specify the number of instances to
  sample when estimating attributes.
  If not specified, then all instances
  will be used.
         -D <seed>
  Seed for randomly sampling instances.
  (Default = 1)
         -K <number of neighbours>
  Number of nearest neighbours (k) used
  to estimate attribute relevances
  (Default = 10).
         -W
  Weight nearest neighbours by distance
         -A <num>
  Specify sigma value (used in an exp
  function to control how quickly
  weights for more distant instances
  decrease. Use in conjunction with -W.
  Sensible value=1/5 to 1/10 of the
  number of nearest neighbours.
  (Default = 2)
        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

      • sigmaTipText

        public java.lang.String sigmaTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setSigma

        public void setSigma​(int s)
              throws java.lang.Exception
        Sets the sigma value.
        Parameters:
        s - the value of sigma (> 0)
        Throws:
        java.lang.Exception - if s is not positive

      • getSigma

        public int getSigma()
        Get the value of sigma.
        Returns:
        the sigma value.

      • numNeighboursTipText

        public java.lang.String numNeighboursTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setNumNeighbours

        public void setNumNeighbours​(int n)
        Set the number of nearest neighbours
        Parameters:
        n - the number of nearest neighbours.

      • getNumNeighbours

        public int getNumNeighbours()
        Get the number of nearest neighbours
        Returns:
        the number of nearest neighbours

      • seedTipText

        public java.lang.String seedTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setSeed

        public void setSeed​(int s)
        Set the random number seed for randomly sampling instances.
        Parameters:
        s - the random number seed.

      • getSeed

        public int getSeed()
        Get the seed used for randomly sampling instances.
        Returns:
        the random number seed.

      • sampleSizeTipText

        public java.lang.String sampleSizeTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setSampleSize

        public void setSampleSize​(int s)
        Set the number of instances to sample for attribute estimation
        Parameters:
        s - the number of instances to sample.

      • getSampleSize

        public int getSampleSize()
        Get the number of instances used for estimating attributes
        Returns:
        the number of instances.

      • weightByDistanceTipText

        public java.lang.String weightByDistanceTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setWeightByDistance

        public void setWeightByDistance​(boolean b)
        Set the nearest neighbour weighting method
        Parameters:
        b - true nearest neighbours are to be weighted by distance.

      • getWeightByDistance

        public boolean getWeightByDistance()
        Get whether nearest neighbours are being weighted by distance
        Returns:
        m_weightByDiffernce

      • getOptions

        public java.lang.String[] getOptions()
        Gets the current settings of ReliefFAttributeEval.
        Specified by:
        getOptions in interface OptionHandler
        Returns:
        an array of strings suitable for passing to setOptions()

      • toString

        public java.lang.String toString()
        Return a description of the ReliefF attribute evaluator.
        Overrides:
        toString in class java.lang.Object
        Returns:
        a description of the evaluator as a String.

      • buildEvaluator

        public void buildEvaluator​(Instances data)
                    throws java.lang.Exception
        Initializes a ReliefF attribute evaluator.
        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 using ReliefF's instance based approach. The actual work is done by buildEvaluator which evaluates all features.
        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

      • 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