weka.datagenerators.clusterers

Class SubspaceCluster

java.lang.Object

weka.datagenerators.DataGenerator

weka.datagenerators.ClusterGenerator

weka.datagenerators.clusterers.SubspaceCluster

All Implemented Interfaces:

java.io.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: 15748 $

Author:

Gabi Schmidberger (gabi@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static int	CONTINUOUS cluster subtype: continuous
static int	GAUSSIAN cluster type: gaussian
static int	INTEGER cluster subtype: integer
static Tag[]	TAGS_CLUSTERSUBTYPE the tags for the cluster types
static Tag[]	TAGS_CLUSTERTYPE the tags for the cluster types
static int	TOTAL_UNIFORM cluster type: total uniform
static int	UNIFORM_RANDOM cluster type: uniform/random

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method and Description
java.lang.String	booleanColsTipText() Returns the tip text for this property
java.lang.String	clusterDefinitionsTipText() Returns the tip text for this property
Instances	defineDataFormat() Initializes the format for the dataset produced.
Instance	generateExample() Generate an example of the dataset.
Instances	generateExamples() Generate all examples of the dataset.
java.lang.String	generateFinished() Compiles documentation about the data generation after the generation process
java.lang.String	generateStart() Compiles documentation about the data generation before the generation process
Range	getBooleanCols() returns the range of boolean attributes.
ClusterDefinition[]	getClusterDefinitions() returns the currently set clusters
Range	getNominalCols() returns the range of nominal attributes
int[]	getNumValues() returns array that stores the number of values for a nominal attribute.
java.lang.String[]	getOptions() Gets the current settings of the datagenerator.
java.lang.String	getRevision() Returns the revision string.
boolean	getSingleModeFlag() Gets the single mode flag.
java.lang.String	globalInfo() Returns a string describing this data generator.
boolean	isBoolean(int index) Returns true if attribute is boolean
boolean	isNominal(int index) Returns true if attribute is nominal
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	main(java.lang.String[] args) Main method for testing this class.
java.lang.String	nominalColsTipText() Returns the tip text for this property
void	setBooleanCols(Range value) Sets which attributes are boolean.
void	setBooleanIndices(java.lang.String rangeList) Sets which attributes are boolean
void	setClusterDefinitions(ClusterDefinition[] value) sets the clusters to use
void	setNominalCols(Range value) Sets which attributes are nominal.
void	setNominalIndices(java.lang.String rangeList) Sets which attributes are nominal
void	setOptions(java.lang.String[] options) Parses a list of options for this object.

Methods inherited from class weka.datagenerators.ClusterGenerator

classFlagTipText, getClassFlag, getNumAttributes, numAttributesTipText, setClassFlag, setNumAttributes

Methods inherited from class weka.datagenerators.DataGenerator

debugTipText, defaultOutput, enumToVector, formatTipText, getDatasetFormat, getDebug, getEpilogue, getNumExamplesAct, getOutput, getPrologue, getRandom, getRelationName, getSeed, makeData, outputTipText, randomTipText, relationNameTipText, runDataGenerator, seedTipText, setDatasetFormat, setDebug, setOutput, setRandom, setRelationName, setSeed

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

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

GAUSSIAN

public static final int GAUSSIAN

cluster type: gaussian

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

INTEGER

public static final int INTEGER

cluster subtype: integer

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 java.lang.String globalInfo()

Returns a string describing this data generator.

Returns:

a description of the data generator suitable for displaying in the explorer/experimenter gui

listOptions

public java.util.Enumeration<Option> listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class ClusterGenerator

Returns:

an enumeration of all the available options

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.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:

java.lang.Exception - if an option is not supported

setBooleanIndices

public void setBooleanIndices(java.lang.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:

java.lang.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 java.lang.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(java.lang.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:

java.lang.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 java.lang.String nominalColsTipText()

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 the datagenerator.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class ClusterGenerator

Returns:

an array of strings suitable for passing to setOptions

See Also:

DataGenerator.removeBlacklist(String[])

getClusterDefinitions

public ClusterDefinition[] getClusterDefinitions()

returns the currently set clusters

Returns:

the currently set clusters

setClusterDefinitions

public void setClusterDefinitions(ClusterDefinition[] value)
                           throws java.lang.Exception

sets the clusters to use

Parameters:

value - the clusters do use

Throws:

java.lang.Exception - if clusters are not the correct class

clusterDefinitionsTipText

public java.lang.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.

defineDataFormat

public Instances defineDataFormat()
                           throws java.lang.Exception

Initializes the format for the dataset produced.

Overrides:

defineDataFormat in class DataGenerator

Returns:

the output data format

Throws:

java.lang.Exception - data format could not be defined

See Also:

DataGenerator.defaultRelationName()

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 java.lang.Exception

Generate an example of the dataset.

Specified by:

generateExample in class DataGenerator

Returns:

the instance generated

Throws:

java.lang.Exception - if format not defined or generating
examples one by one is not possible, because voting is chosen

generateExamples

public Instances generateExamples()
                           throws java.lang.Exception

Generate all examples of the dataset.

Specified by:

generateExamples in class DataGenerator

Returns:

the instance generated

Throws:

java.lang.Exception - if format not defined

generateFinished

public java.lang.String generateFinished()
                                  throws java.lang.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:

java.lang.Exception - no input structure has been defined

generateStart

public java.lang.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 java.lang.String getRevision()

Returns the revision string.

Returns:

the revision

main

public static void main(java.lang.String[] args)

Main method for testing this class.

Parameters:

args - should contain arguments for the data producer: