Package weka.attributeSelection

Class CfsSubsetEval

  • All Implemented Interfaces:
    java.io.Serializable, SubsetEvaluator, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler, TechnicalInformationHandler, ThreadSafe
    public class CfsSubsetEval
extends ASEvaluation
implements SubsetEvaluator, ThreadSafe, OptionHandler, TechnicalInformationHandler
    CfsSubsetEval :

    Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.

    Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.

    For more information see:

    M. A. Hall (1998). Correlation-based Feature Subset Selection for Machine Learning. Hamilton, New Zealand.

    BibTeX: 

     @phdthesis{Hall1998,
    address = {Hamilton, New Zealand},
    author = {M. A. Hall},
    school = {University of Waikato},
    title = {Correlation-based Feature Subset Selection for Machine Learning},
    year = {1998}
 }

    Valid options are: 

     -M
  Treat missing values as a separate value.
 
     -L
  Don't include locally predictive attributes.
 
     -Z
  Precompute the full correlation matrix at the outset, rather than compute correlations lazily (as needed) during the search. Use this in conjuction with parallel processing in order to speed up a backward search.
 
     -P <int>
  The size of the thread pool, for example, the number of cores in the CPU. (default 1)
 
     -E <int>
  The number of threads to use, which should be >= size of thread pool. (default 1)
 
     -D
  Output debugging info.
    Version:
    $Revision: 11852 $
    Author:
    Mark Hall (mhall@cs.waikato.ac.nz)
    See Also:
    Discretize, Serialized Form

    • Constructor Detail

      • CfsSubsetEval

        public CfsSubsetEval()
        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<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 and sets a given list of options.

        Valid options are: 

         -M
  Treat missing values as a separate value.
 
         -L
  Don't include locally predictive attributes.
 
         -Z
  Precompute the full correlation matrix at the outset, rather than compute correlations lazily (as needed) during the search. Use this in conjuction with parallel processing in order to speed up a backward search.
 
         -P <int>
  The size of the thread pool, for example, the number of cores in the CPU. (default 1)
 
         -E <int>
  The number of threads to use, which should be >= size of thread pool. (default 1)
 
         -D
  Output debugging info.
        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

      • preComputeCorrelationMatrixTipText

        public java.lang.String preComputeCorrelationMatrixTipText()
        Returns:
        a string to describe the option

      • setPreComputeCorrelationMatrix

        public void setPreComputeCorrelationMatrix​(boolean p)
        Set whether to pre-compute the full correlation matrix at the outset, rather than computing individual correlations lazily (as needed) during the search.
        Parameters:
        p - true if the correlation matrix is to be pre-computed at the outset

      • getPreComputeCorrelationMatrix

        public boolean getPreComputeCorrelationMatrix()
        Get whether to pre-compute the full correlation matrix at the outset, rather than computing individual correlations lazily (as needed) during the search.
        Returns:
        true if the correlation matrix is to be pre-computed at the outset

      • numThreadsTipText

        public java.lang.String numThreadsTipText()
        Returns:
        a string to describe the option

      • getNumThreads

        public int getNumThreads()
        Gets the number of threads.

      • setNumThreads

        public void setNumThreads​(int nT)
        Sets the number of threads

      • poolSizeTipText

        public java.lang.String poolSizeTipText()
        Returns:
        a string to describe the option

      • getPoolSize

        public int getPoolSize()
        Gets the number of threads.

      • setPoolSize

        public void setPoolSize​(int nT)
        Sets the number of threads

      • locallyPredictiveTipText

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

      • setLocallyPredictive

        public void setLocallyPredictive​(boolean b)
        Include locally predictive attributes
        Parameters:
        b - true or false

      • getLocallyPredictive

        public boolean getLocallyPredictive()
        Return true if including locally predictive attributes
        Returns:
        true if locally predictive attributes are to be used

      • missingSeparateTipText

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

      • setMissingSeparate

        public void setMissingSeparate​(boolean b)
        Treat missing as a separate value
        Parameters:
        b - true or false

      • getMissingSeparate

        public boolean getMissingSeparate()
        Return true is missing is treated as a separate value
        Returns:
        true if missing is to be treated as a separate value

      • setDebug

        public void setDebug​(boolean d)
        Set whether to output debugging info
        Parameters:
        d - true if debugging info is to be output

      • getDebug

        public boolean getDebug()
        Set whether to output debugging info
        Returns:
        true if debugging info is to be output

      • debugTipText

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

      • getOptions

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

      • buildEvaluator

        public void buildEvaluator​(Instances data)
                    throws java.lang.Exception
        Generates a attribute evaluator. Has to initialize all fields of the evaluator that are not being set via options. CFS also discretises attributes (if necessary) and initializes the correlation matrix.
        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

      • evaluateSubset

        public double evaluateSubset​(java.util.BitSet subset)
                      throws java.lang.Exception
        evaluates a subset of attributes
        Specified by:
        evaluateSubset in interface SubsetEvaluator
        Parameters:
        subset - a bitset representing the attribute subset to be evaluated
        Returns:
        the merit
        Throws:
        java.lang.Exception - if the subset could not be evaluated

      • toString

        public java.lang.String toString()
        returns a string describing CFS
        Overrides:
        toString in class java.lang.Object
        Returns:
        the description as a string

      • postProcess

        public int[] postProcess​(int[] attributeSet)
                  throws java.lang.Exception
        Calls locallyPredictive in order to include locally predictive attributes (if requested).
        Overrides:
        postProcess in class ASEvaluation
        Parameters:
        attributeSet - the set of attributes found by the search
        Returns:
        a possibly ranked list of postprocessed attributes
        Throws:
        java.lang.Exception - if postprocessing fails for some reason

      • clean

        public void clean()
        Description copied from class: ASEvaluation
        Tells the evaluator that the attribute selection process is complete. It can then clean up data structures, references to training data as necessary in order to save memory
        Overrides:
        clean in class ASEvaluation

      • main

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