weka.clusterers

Class CLOPE

java.lang.Object

weka.clusterers.AbstractClusterer

weka.clusterers.CLOPE

All Implemented Interfaces:

Serializable, Cloneable, Clusterer, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class CLOPE
extends AbstractClusterer
implements OptionHandler, TechnicalInformationHandler

Yiling Yang, Xudong Guan, Jinyuan You: CLOPE: a fast and effective clustering algorithm for transactional data. In: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, 682-687, 2002.

BibTeX:

 @inproceedings{Yang2002,
    author = {Yiling Yang and Xudong Guan and Jinyuan You},
    booktitle = {Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining},
    pages = {682-687},
    publisher = {ACM  New York, NY, USA},
    title = {CLOPE: a fast and effective clustering algorithm for transactional data},
    year = {2002}
 }
 

Valid options are:

 -R <num>
  Repulsion
  (default 2.6)

Version:

$Revision: 5538 $

Author:

Alexander Smirnov ([email protected])

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
ArrayList<weka.clusterers.CLOPE.CLOPECluster>	clusters Array of clusters

Constructor Summary

Constructors

Constructor and Description
CLOPE() the default constructor

Method Summary

Methods

Modifier and Type	Method and Description
int	AddInstanceToBestCluster(Instance inst) Add instance to best cluster
void	buildClusterer(Instances data) Generate Clustering via CLOPE
int	clusterInstance(Instance instance) Classifies a given instance.
Capabilities	getCapabilities() Returns default capabilities of the clusterer.
String[]	getOptions() Gets the current settings of CLOPE
double	getRepulsion() gets the repulsion
String	getRevision() Returns the revision string.
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.
String	globalInfo() Returns a string describing this DataMining-Algorithm
Enumeration	listOptions() Returns an enumeration of all the available options..
static void	main(String[] argv) Main method for testing this class.
int	MoveInstanceToBestCluster(Instance inst) Move instance to best cluster
int	numberOfClusters() Returns the number of clusters.
String	repulsionTipText() Returns the tip text for this property
void	setOptions(String[] options) Parses a given list of options.
void	setRepulsion(double value) set the repulsion
String	toString() return a string describing this clusterer

Methods inherited from class weka.clusterers.AbstractClusterer

distributionForInstance, forName, makeCopies, makeCopy

Methods inherited from class java.lang.Object

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

Field Detail

clusters

public ArrayList<weka.clusterers.CLOPE.CLOPECluster> clusters

Array of clusters

Constructor Detail

CLOPE

public CLOPE()

the default constructor

Method Detail

numberOfClusters

public int numberOfClusters()

Description copied from class: AbstractClusterer

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.

listOptions

public Enumeration listOptions()

Description copied from interface: OptionHandler

Returns an enumeration of all the available options..

Specified by:

listOptions in interface OptionHandler

Returns:

an enumeration of all available options.

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options.

Valid options are:

 -R <num>
  Repulsion
  (default 2.6)

Specified by:

setOptions in interface OptionHandler

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

public String[] getOptions()

Gets the current settings of CLOPE

Specified by:

getOptions in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions()

repulsionTipText

public String repulsionTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setRepulsion

public void setRepulsion(double value)

set the repulsion

Parameters:

value - the repulsion

Throws:

Exception - if number of clusters is negative

getRepulsion

public double getRepulsion()

gets the repulsion

Returns:

the repulsion

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the clusterer.

Specified by:

getCapabilities in interface Clusterer

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class AbstractClusterer

Returns:

the capabilities of this clusterer

See Also:

Capabilities

buildClusterer

public void buildClusterer(Instances data)
                    throws Exception

Generate Clustering via CLOPE

Specified by:

buildClusterer in interface Clusterer

Specified by:

buildClusterer in class AbstractClusterer

Parameters:

instances - The instances that need to be clustered

Throws:

Exception - If clustering was not successful

AddInstanceToBestCluster

public int AddInstanceToBestCluster(Instance inst)

Add instance to best cluster

MoveInstanceToBestCluster

public int MoveInstanceToBestCluster(Instance inst)

Move instance to best cluster

clusterInstance

public int clusterInstance(Instance instance)
                    throws Exception

Classifies a given instance.

Specified by:

clusterInstance in interface Clusterer

Overrides:

clusterInstance in class AbstractClusterer

Parameters:

instance - The instance to be assigned to a cluster

Returns:

int The number of the assigned cluster as an integer

Throws:

Exception - If instance could not be clustered successfully

toString

public String toString()

return a string describing this clusterer

Overrides:

toString in class Object

Returns:

a description of the clusterer as a string

globalInfo

public String globalInfo()

Returns a string describing this DataMining-Algorithm

Returns:

String Information for the gui-explorer

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

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClusterer

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - should contain the following arguments:

-t training file [-R repulsion]