Package weka.datagenerators.clusterers

Class SubspaceCluster

  • All Implemented Interfaces:
    Serializable, OptionHandler, Randomizable, RevisionHandler
    public class SubspaceCluster
extends ClusterGenerator
    A data generator that produces data points in hyperrectangular subspace clusters.

    Valid options are: 

     -h
  Prints this help.
 
     -o <file>
  The name of the output file, otherwise the generated data is
  printed to stdout.
 
     -r <name>
  The name of the relation.
 
     -d
  Whether to print debug informations.
 
     -S
  The seed for random function (default 1)
 
     -a <num>
  The number of attributes (default 1).
 
     -c
  Class Flag, if set, the cluster is listed in extra attribute.
 
     -b <range>
  The indices for boolean attributes.
 
     -m <range>
  The indices for nominal attributes.
 
     -C <cluster-definition>
  A cluster definition of class 'SubspaceClusterDefinition'
  (definition needs to be quoted to be recognized as 
  a single argument).
 
     Options specific to weka.datagenerators.clusterers.SubspaceClusterDefinition:
 
     -A <range>
  Uses a random uniform distribution for the instances in the cluster.
 
     -U <range>
  Generates totally uniformly distributed instances in the cluster.
 
     -G <range>
  Uses a Gaussian distribution for the instances in the cluster.
 
     -D <num>,<num>
  The attribute min/max (-A and -U) or mean/stddev (-G) for
  the cluster.
 
     -N <num>..<num>
  The range of number of instances per cluster (default 1..50).
 
     -I
  Uses integer instead of continuous values (default continuous).
    Version:
    $Revision$
    Author:
    Gabi Schmidberger (gabi@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Detail

      • UNIFORM_RANDOM

        public static final int UNIFORM_RANDOM
        cluster type: uniform/random
        See Also:
        Constant Field Values

      • TOTAL_UNIFORM

        public static final int TOTAL_UNIFORM
        cluster type: total uniform
        See Also:
        Constant Field Values

      • TAGS_CLUSTERTYPE

        public static final Tag[] TAGS_CLUSTERTYPE
        the tags for the cluster types

      • CONTINUOUS

        public static final int CONTINUOUS
        cluster subtype: continuous
        See Also:
        Constant Field Values

      • TAGS_CLUSTERSUBTYPE

        public static final Tag[] TAGS_CLUSTERSUBTYPE
        the tags for the cluster types

    • Constructor Detail

      • SubspaceCluster

        public SubspaceCluster()
        initializes the generator, sets the number of clusters to 0, since user has to specify them explicitly

    • Method Detail

      • globalInfo

        public String globalInfo()
        Returns a string describing this data generator.
        Returns:
        a description of the data generator suitable for displaying in the explorer/experimenter gui

      • setOptions

        public void setOptions​(String[] options)
                throws Exception
        Parses a list of options for this object.

        Valid options are: 

         -h
  Prints this help.
 
         -o <file>
  The name of the output file, otherwise the generated data is
  printed to stdout.
 
         -r <name>
  The name of the relation.
 
         -d
  Whether to print debug informations.
 
         -S
  The seed for random function (default 1)
 
         -a <num>
  The number of attributes (default 1).
 
         -c
  Class Flag, if set, the cluster is listed in extra attribute.
 
         -b <range>
  The indices for boolean attributes.
 
         -m <range>
  The indices for nominal attributes.
 
         -C <cluster-definition>
  A cluster definition of class 'SubspaceClusterDefinition'
  (definition needs to be quoted to be recognized as 
  a single argument).
 
         Options specific to weka.datagenerators.clusterers.SubspaceClusterDefinition:
 
         -A <range>
  Uses a random uniform distribution for the instances in the cluster.
 
         -U <range>
  Generates totally uniformly distributed instances in the cluster.
 
         -G <range>
  Uses a Gaussian distribution for the instances in the cluster.
 
         -D <num>,<num>
  The attribute min/max (-A and -U) or mean/stddev (-G) for
  the cluster.
 
         -N <num>..<num>
  The range of number of instances per cluster (default 1..50).
 
         -I
  Uses integer instead of continuous values (default continuous).
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class ClusterGenerator
        Parameters:
        options - the list of options as an array of strings
        Throws:
        Exception - if an option is not supported

      • setBooleanIndices

        public void setBooleanIndices​(String rangeList)
        Sets which attributes are boolean
        Parameters:
        rangeList - a string representing the list of attributes. Since the string will typically come from a user, attributes are indexed from 1.
        eg: first-3,5,6-last
        Throws:
        IllegalArgumentException - if an invalid range list is supplied

      • setBooleanCols

        public void setBooleanCols​(Range value)
        Sets which attributes are boolean.
        Parameters:
        value - the range to use

      • getBooleanCols

        public Range getBooleanCols()
        returns the range of boolean attributes.
        Returns:
        the range of boolean attributes

      • booleanColsTipText

        public String booleanColsTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setNominalIndices

        public void setNominalIndices​(String rangeList)
        Sets which attributes are nominal
        Parameters:
        rangeList - a string representing the list of attributes. Since the string will typically come from a user, attributes are indexed from 1.
        eg: first-3,5,6-last
        Throws:
        IllegalArgumentException - if an invalid range list is supplied

      • setNominalCols

        public void setNominalCols​(Range value)
        Sets which attributes are nominal.
        Parameters:
        value - the range to use

      • getNominalCols

        public Range getNominalCols()
        returns the range of nominal attributes
        Returns:
        the range of nominal attributes

      • nominalColsTipText

        public String nominalColsTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • getClusterDefinitions

        public ClusterDefinition[] getClusterDefinitions()
        returns the currently set clusters
        Returns:
        the currently set clusters

      • setClusterDefinitions

        public void setClusterDefinitions​(ClusterDefinition[] value)
                           throws Exception
        sets the clusters to use
        Parameters:
        value - the clusters do use
        Throws:
        Exception - if clusters are not the correct class

      • clusterDefinitionsTipText

        public String clusterDefinitionsTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • getSingleModeFlag

        public boolean getSingleModeFlag()
        Gets the single mode flag.
        Specified by:
        getSingleModeFlag in class DataGenerator
        Returns:
        true if methode generateExample can be used.

      • isBoolean

        public boolean isBoolean​(int index)
        Returns true if attribute is boolean
        Parameters:
        index - of the attribute
        Returns:
        true if the attribute is boolean

      • isNominal

        public boolean isNominal​(int index)
        Returns true if attribute is nominal
        Parameters:
        index - of the attribute
        Returns:
        true if the attribute is nominal

      • getNumValues

        public int[] getNumValues()
        returns array that stores the number of values for a nominal attribute.
        Returns:
        the array that stores the number of values for a nominal attribute

      • generateExample

        public Instance generateExample()
                         throws Exception
        Generate an example of the dataset.
        Specified by:
        generateExample in class DataGenerator
        Returns:
        the instance generated
        Throws:
        Exception - if format not defined or generating
        examples one by one is not possible, because voting is chosen

      • generateFinished

        public String generateFinished()
                        throws Exception
        Compiles documentation about the data generation after the generation process
        Specified by:
        generateFinished in class DataGenerator
        Returns:
        string with additional information about generated dataset
        Throws:
        Exception - no input structure has been defined

      • generateStart

        public String generateStart()
        Compiles documentation about the data generation before the generation process
        Specified by:
        generateStart in class DataGenerator
        Returns:
        string with additional information

      • getRevision

        public String getRevision()
        Returns the revision string.
        Returns:
        the revision

      • main

        public static void main​(String[] args)
        Main method for testing this class.
        Parameters:
        args - should contain arguments for the data producer: