Package weka.attributeSelection

Class LatentSemanticAnalysis

  • All Implemented Interfaces:
    java.io.Serializable, AttributeEvaluator, AttributeTransformer, CapabilitiesHandler, OptionHandler, RevisionHandler
    public class LatentSemanticAnalysis
extends UnsupervisedAttributeEvaluator
implements AttributeTransformer, OptionHandler
    Performs latent semantic analysis and transformation of the data. Use in conjunction with a Ranker search. A low-rank approximation of the full data is found by specifying the number of singular values to use. The dataset may be transformed to give the relation of either the attributes or the instances (default) to the concept space created by the transformation.

    Valid options are: 

     -N
  Normalize input data.
     -R
  Rank approximation used in LSA. May be actual number of 
  LSA attributes to include (if greater than 1) or a proportion 
  of total singular values to account for (if between 0 and 1). 
  A value less than or equal to zero means use all latent variables.
  (default = 0.95)
     -A
  Maximum number of attributes to include in 
  transformed attribute names. (-1 = include all)
    Version:
    $Revision: 11821 $
    Author:
    Amri Napolitano
    See Also:
    Serialized Form

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      void buildEvaluator​(Instances data)
      Initializes the singular values/vectors and performs the analysis
      Instance convertInstance​(Instance instance)
      Transform an instance in original (unnormalized) format
      double evaluateAttribute​(int att)
      Evaluates the merit of a transformed attribute.
      Capabilities getCapabilities()
      Returns the capabilities of this evaluator.
      int getMaximumAttributeNames()
      Gets maximum number of attributes to include in transformed attribute names.
      boolean getNormalize()
      Gets whether or not input data is to be normalized
      java.lang.String[] getOptions()
      Gets the current settings of LatentSemanticAnalysis
      double getRank()
      Gets the desired matrix rank (or coverage proportion) for feature-space reduction
      java.lang.String getRevision()
      Returns the revision string.
      java.lang.String globalInfo()
      Returns a string describing this attribute transformer
      java.util.Enumeration listOptions()
      Returns an enumeration describing the available options.
      static void main​(java.lang.String[] argv)
      Main method for testing this class
      java.lang.String maximumAttributeNamesTipText()
      Returns the tip text for this property
      java.lang.String normalizeTipText()
      Returns the tip text for this property
      java.lang.String rankTipText()
      Returns the tip text for this property
      void setMaximumAttributeNames​(int newMaxAttributes)
      Sets maximum number of attributes to include in transformed attribute names.
      void setNormalize​(boolean newNormalize)
      Set whether input data will be normalized.
      void setOptions​(java.lang.String[] options)
      Parses a given list of options.
      void setRank​(double newRank)
      Sets the desired matrix rank (or coverage proportion) for feature-space reduction
      java.lang.String toString()
      Returns a description of this attribute transformer
      Instances transformedData​(Instances data)
      Transform the supplied data set (assumed to be the same format as the training data)
      Instances transformedHeader()
      Returns just the header for the transformed data (ie.

      • Methods inherited from class java.lang.Object

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

    • Constructor Detail

      • LatentSemanticAnalysis

        public LatentSemanticAnalysis()

    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing this attribute transformer
        Returns:
        a description of the evaluator suitable for displaying in the explorer/experimenter gui

      • 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: 

         -N
  Normalize input data.
         -R
  Rank approximation used in LSA. May be actual number of 
  LSA attributes to include (if greater than 1) or a proportion 
  of total singular values to account for (if between 0 and 1). 
  A value less than or equal to zero means use all latent variables.
  (default = 0.95)
         -A
  Maximum number of attributes to include in 
  transformed attribute names. (-1 = include all)
        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

      • normalizeTipText

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

      • setNormalize

        public void setNormalize​(boolean newNormalize)
        Set whether input data will be normalized.
        Parameters:
        newNormalize - true if input data is to be normalized

      • getNormalize

        public boolean getNormalize()
        Gets whether or not input data is to be normalized
        Returns:
        true if input data is to be normalized

      • rankTipText

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

      • setRank

        public void setRank​(double newRank)
        Sets the desired matrix rank (or coverage proportion) for feature-space reduction
        Parameters:
        newRank - the desired rank (or coverage) for feature-space reduction

      • getRank

        public double getRank()
        Gets the desired matrix rank (or coverage proportion) for feature-space reduction
        Returns:
        the rank (or coverage) for feature-space reduction

      • maximumAttributeNamesTipText

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

      • setMaximumAttributeNames

        public void setMaximumAttributeNames​(int newMaxAttributes)
        Sets maximum number of attributes to include in transformed attribute names.
        Parameters:
        newMaxAttributes - the maximum number of attributes

      • getMaximumAttributeNames

        public int getMaximumAttributeNames()
        Gets maximum number of attributes to include in transformed attribute names.
        Returns:
        the maximum number of attributes

      • getOptions

        public java.lang.String[] getOptions()
        Gets the current settings of LatentSemanticAnalysis
        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
        Initializes the singular values/vectors and performs the analysis
        Specified by:
        buildEvaluator in class ASEvaluation
        Parameters:
        data - the instances to analyse/transform
        Throws:
        java.lang.Exception - if analysis fails

      • transformedHeader

        public Instances transformedHeader()
                            throws java.lang.Exception
        Returns just the header for the transformed data (ie. an empty set of instances. This is so that AttributeSelection can determine the structure of the transformed data without actually having to get all the transformed data through getTransformedData().
        Specified by:
        transformedHeader in interface AttributeTransformer
        Returns:
        the header of the transformed data.
        Throws:
        java.lang.Exception - if the header of the transformed data can't be determined.

      • transformedData

        public Instances transformedData​(Instances data)
                          throws java.lang.Exception
        Transform the supplied data set (assumed to be the same format as the training data)
        Specified by:
        transformedData in interface AttributeTransformer
        Returns:
        the transformed training data
        Throws:
        java.lang.Exception - if transformed data can't be returned

      • evaluateAttribute

        public double evaluateAttribute​(int att)
                         throws java.lang.Exception
        Evaluates the merit of a transformed attribute. This is defined to be the square of the singular value for the latent variable corresponding to the transformed attribute.
        Specified by:
        evaluateAttribute in interface AttributeEvaluator
        Parameters:
        att - the attribute to be evaluated
        Returns:
        the merit of a transformed attribute
        Throws:
        java.lang.Exception - if attribute can't be evaluated

      • convertInstance

        public Instance convertInstance​(Instance instance)
                         throws java.lang.Exception
        Transform an instance in original (unnormalized) format
        Specified by:
        convertInstance in interface AttributeTransformer
        Parameters:
        instance - an instance in the original (unnormalized) format
        Returns:
        a transformed instance
        Throws:
        java.lang.Exception - if instance can't be transformed

      • toString

        public java.lang.String toString()
        Returns a description of this attribute transformer
        Overrides:
        toString in class java.lang.Object
        Returns:
        a String describing this attribute transformer

      • main

        public static void main​(java.lang.String[] argv)
        Main method for testing this class
        Parameters:
        argv - should contain the command line arguments to the evaluator/transformer (see AttributeSelection)