Package weka.clusterers

Class MakeDensityBasedClusterer

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, Clusterer, DensityBasedClusterer, NumberOfClustersRequestable, CapabilitiesHandler, OptionHandler, RevisionHandler, WeightedInstancesHandler
    public class MakeDensityBasedClusterer
extends AbstractDensityBasedClusterer
implements NumberOfClustersRequestable, OptionHandler, WeightedInstancesHandler
    Class for wrapping a Clusterer to make it return a distribution and density. Fits normal distributions and discrete distributions within each cluster produced by the wrapped clusterer. Supports the NumberOfClustersRequestable interface only if the wrapped Clusterer does.

    Valid options are: 

     -M <num>
  minimum allowable standard deviation for normal density computation 
  (default 1e-6)
     -W <clusterer name>
  Clusterer to wrap.
  (default weka.clusterers.SimpleKMeans)
     
 Options specific to clusterer weka.clusterers.SimpleKMeans:
 
     -N <num>
  number of clusters.
  (default 2).
     -V
  Display std. deviations for centroids.
 
     -M
  Replace missing values with mean/mode.
 
     -S <num>
  Random number seed.
  (default 10)
    Options after "--" are passed on to the base clusterer.
    Version:
    $Revision: 5538 $
    Author:
    Richard Kirkby (rkirkby@cs.waikato.ac.nz), Mark Hall (mhall@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
    See Also:
    Serialized Form

    • Constructor Detail

      • MakeDensityBasedClusterer

        public MakeDensityBasedClusterer()
        Default constructor.

      • MakeDensityBasedClusterer

        public MakeDensityBasedClusterer​(Clusterer toWrap)
        Contructs a MakeDensityBasedClusterer wrapping a given Clusterer.
        Parameters:
        toWrap - the clusterer to wrap around

    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing classifier
        Returns:
        a description suitable for displaying in the explorer/experimenter gui

      • setNumClusters

        public void setNumClusters​(int n)
                    throws java.lang.Exception
        Set the number of clusters to generate.
        Specified by:
        setNumClusters in interface NumberOfClustersRequestable
        Parameters:
        n - the number of clusters to generate
        Throws:
        java.lang.Exception - if the wrapped clusterer has not been set, or if the wrapped clusterer does not implement this facility.

      • buildClusterer

        public void buildClusterer​(Instances data)
                    throws java.lang.Exception
        Builds a clusterer for a set of instances.
        Specified by:
        buildClusterer in interface Clusterer
        Specified by:
        buildClusterer in class AbstractClusterer
        Parameters:
        data - the instances to train the clusterer with
        Throws:
        java.lang.Exception - if the clusterer hasn't been set or something goes wrong

      • numberOfClusters

        public int numberOfClusters()
                     throws java.lang.Exception
        Returns the number of clusters.
        Specified by:
        numberOfClusters in interface Clusterer
        Specified by:
        numberOfClusters in class AbstractClusterer
        Returns:
        the number of clusters generated for a training dataset.
        Throws:
        java.lang.Exception - if number of clusters could not be returned successfully

      • toString

        public java.lang.String toString()
        Returns a description of the clusterer.
        Overrides:
        toString in class java.lang.Object
        Returns:
        a string containing a description of the clusterer

      • clustererTipText

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

      • setClusterer

        public void setClusterer​(Clusterer toWrap)
        Sets the clusterer to wrap.
        Parameters:
        toWrap - the clusterer

      • getClusterer

        public Clusterer getClusterer()
        Gets the clusterer being wrapped.
        Returns:
        the clusterer

      • minStdDevTipText

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

      • setMinStdDev

        public void setMinStdDev​(double m)
        Set the minimum value for standard deviation when calculating normal density. Reducing this value can help prevent arithmetic overflow resulting from multiplying large densities (arising from small standard deviations) when there are many singleton or near singleton values.
        Parameters:
        m - minimum value for standard deviation

      • getMinStdDev

        public double getMinStdDev()
        Get the minimum allowable standard deviation.
        Returns:
        the minumum allowable standard deviation

      • 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>
  minimum allowable standard deviation for normal density computation 
  (default 1e-6)
         -W <clusterer name>
  Clusterer to wrap.
  (default weka.clusterers.SimpleKMeans)
         
 Options specific to clusterer weka.clusterers.SimpleKMeans:
 
         -N <num>
  number of clusters.
  (default 2).
         -V
  Display std. deviations for centroids.
 
         -M
  Replace missing values with mean/mode.
 
         -S <num>
  Random number seed.
  (default 10)
        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()
        Gets the current settings of the clusterer.
        Specified by:
        getOptions in interface OptionHandler
        Returns:
        an array of strings suitable for passing to setOptions()

      • main

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