Class LeastMedSq

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

    public class LeastMedSq
    extends Classifier
    implements OptionHandler, TechnicalInformationHandler
    Implements a least median sqaured linear regression utilising the existing weka LinearRegression class to form predictions.
    Least squared regression functions are generated from random subsamples of the data. The least squared regression with the lowest meadian squared error is chosen as the final model.

    The basis of the algorithm is

    Peter J. Rousseeuw, Annick M. Leroy (1987). Robust regression and outlier detection. .

    BibTeX:

     @book{Rousseeuw1987,
        author = {Peter J. Rousseeuw and Annick M. Leroy},
        title = {Robust regression and outlier detection},
        year = {1987}
     }
     

    Valid options are:

     -S <sample size>
      Set sample size
      (default: 4)
     
     -G <seed>
      Set the seed used to generate samples
      (default: 0)
     
     -D
      Produce debugging output
      (default no debugging output)
     
    Version:
    $Revision: 5523 $
    Author:
    Tony Voyle (tv6@waikato.ac.nz)
    See Also:
    Serialized Form
    • Constructor Summary

      Constructors 
      Constructor Description
      LeastMedSq()  
    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      void buildClassifier​(Instances data)
      Build lms regression
      double classifyInstance​(Instance instance)
      Classify a given instance using the best generated LinearRegression Classifier.
      static int combinations​(int n, int r)
      Produces the combination nCr
      Capabilities getCapabilities()
      Returns default capabilities of the classifier.
      boolean getDebug()
      Returns whether or not debugging output shouild be printed
      java.lang.String[] getOptions()
      Gets the current option settings for the OptionHandler.
      long getRandomSeed()
      get the seed for the random number generator
      java.lang.String getRevision()
      Returns the revision string.
      int getSampleSize()
      gets number of samples
      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.
      java.lang.String globalInfo()
      Returns a string describing this classifier
      java.util.Enumeration listOptions()
      Returns an enumeration of all the available options..
      static void main​(java.lang.String[] argv)
      generate a Linear regression predictor for testing
      java.lang.String randomSeedTipText()
      Returns the tip text for this property
      java.lang.String sampleSizeTipText()
      Returns the tip text for this property
      void setDebug​(boolean debug)
      sets whether or not debugging output shouild be printed
      void setOptions​(java.lang.String[] options)
      Sets the OptionHandler's options using the given list.
      void setRandomSeed​(long randomseed)
      Set the seed for the random number generator
      void setSampleSize​(int samplesize)
      sets number of samples
      java.lang.String toString()
      Returns a string representing the best LinearRegression classifier found.
      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
    • Constructor Detail

      • LeastMedSq

        public LeastMedSq()
    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing this classifier
        Returns:
        a description of the classifier 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
      • buildClassifier

        public void buildClassifier​(Instances data)
                             throws java.lang.Exception
        Build lms regression
        Specified by:
        buildClassifier in class Classifier
        Parameters:
        data - training data
        Throws:
        java.lang.Exception - if an error occurs
      • classifyInstance

        public double classifyInstance​(Instance instance)
                                throws java.lang.Exception
        Classify a given instance using the best generated LinearRegression Classifier.
        Overrides:
        classifyInstance in class Classifier
        Parameters:
        instance - instance to be classified
        Returns:
        class value
        Throws:
        java.lang.Exception - if an error occurs
      • toString

        public java.lang.String toString()
        Returns a string representing the best LinearRegression classifier found.
        Overrides:
        toString in class java.lang.Object
        Returns:
        String representing the regression
      • 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 samplesize)
        sets number of samples
        Parameters:
        samplesize - value
      • getSampleSize

        public int getSampleSize()
        gets number of samples
        Returns:
        value
      • randomSeedTipText

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

        public void setRandomSeed​(long randomseed)
        Set the seed for the random number generator
        Parameters:
        randomseed - the seed
      • getRandomSeed

        public long getRandomSeed()
        get the seed for the random number generator
        Returns:
        the seed value
      • setDebug

        public void setDebug​(boolean debug)
        sets whether or not debugging output shouild be printed
        Overrides:
        setDebug in class Classifier
        Parameters:
        debug - true if debugging output selected
      • getDebug

        public boolean getDebug()
        Returns whether or not debugging output shouild be printed
        Overrides:
        getDebug in class Classifier
        Returns:
        true if debuging output selected
      • listOptions

        public java.util.Enumeration listOptions()
        Returns an enumeration of all the available options..
        Specified by:
        listOptions in interface OptionHandler
        Overrides:
        listOptions in class Classifier
        Returns:
        an enumeration of all available options.
      • setOptions

        public void setOptions​(java.lang.String[] options)
                        throws java.lang.Exception
        Sets the OptionHandler's options using the given list. All options will be set (or reset) during this call (i.e. incremental setting of options is not possible). Valid options are:

         -S <sample size>
          Set sample size
          (default: 4)
         
         -G <seed>
          Set the seed used to generate samples
          (default: 0)
         
         -D
          Produce debugging output
          (default no debugging output)
         
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class Classifier
        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()
        Gets the current option settings for the OptionHandler.
        Specified by:
        getOptions in interface OptionHandler
        Overrides:
        getOptions in class Classifier
        Returns:
        the list of current option settings as an array of strings
      • combinations

        public static int combinations​(int n,
                                       int r)
                                throws java.lang.Exception
        Produces the combination nCr
        Parameters:
        n -
        r -
        Returns:
        the combination
        Throws:
        java.lang.Exception - if r is greater than n
      • main

        public static void main​(java.lang.String[] argv)
        generate a Linear regression predictor for testing
        Parameters:
        argv - options