weka.clusterers

Class OPTICS

java.lang.Object

weka.clusterers.AbstractClusterer

weka.clusterers.OPTICS

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Clusterer, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class OPTICS
extends AbstractClusterer
implements OptionHandler, TechnicalInformationHandler

Basic implementation of OPTICS clustering algorithm that should *not* be used as a reference for runtime benchmarks: more sophisticated implementations exist! Clustering of new instances is not supported. More info:

Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Joerg Sander: OPTICS: Ordering Points To Identify the Clustering Structure. In: ACM SIGMOD International Conference on Management of Data, 49-60, 1999.

BibTeX:

 @inproceedings{Ankerst1999,
    author = {Mihael Ankerst and Markus M. Breunig and Hans-Peter Kriegel and Joerg Sander},
    booktitle = {ACM SIGMOD International Conference on Management of Data},
    pages = {49-60},
    publisher = {ACM Press},
    title = {OPTICS: Ordering Points To Identify the Clustering Structure},
    year = {1999}
 }
 

Valid options are:

 -E <double>
  epsilon (default = 0.9)

 -M <int>
  minPoints (default = 6)

 -I <String>
  index (database) used for OPTICS (default = weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase)

 -D <String>
  distance-type (default = weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject)

 -F
  write results to OPTICS_#TimeStamp#.TXT - File

 -no-gui
  suppress the display of the GUI after building the clusterer

 -db-output <file>
  The file to save the generated database to. If a directory
  is provided, the database doesn't get saved.
  The generated file can be viewed with the OPTICS Visualizer:
    java weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.OPTICS_Visualizer [file.ser]
  (default: .)

Version:

$Revision: 9434 $

Author:

Matthias Schubert (schubert@dbs.ifi.lmu.de), Zhanna Melnikova-Albrecht (melnikov@cip.ifi.lmu.de), Rainer Holzmann (holzmann@cip.ifi.lmu.de)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
OPTICS()

Method Summary

Modifier and Type	Method and Description
void	buildClusterer(Instances instances) Generate Clustering via OPTICS
int	clusterInstance(Instance instance) Classifies a given instance.
java.lang.String	database_distanceTypeTipText() Returns the tip text for this property
java.lang.String	database_TypeTipText() Returns the tip text for this property
Database	databaseForName(java.lang.String database_Type, Instances instances) Returns a new Class-Instance of the specified database
java.lang.String	databaseOutputTipText() Returns the tip text for this property.
DataObject	dataObjectForName(java.lang.String database_distanceType, Instance instance, java.lang.String key, Database database) Returns a new Class-Instance of the specified database
java.lang.String	epsilonTipText() Returns the tip text for this property
Capabilities	getCapabilities() Returns default capabilities of the clusterer.
java.lang.String	getDatabase_distanceType() Returns the distance-type
java.lang.String	getDatabase_Type() Returns the type of the used index (database)
java.io.File	getDatabaseOutput() Returns the file to save the database to - if directory, database is not saved.
double	getEpsilon() Returns the value of epsilon
int	getMinPoints() Returns the value of minPoints
java.lang.String[]	getOptions() Gets the current option settings for the OptionHandler.
FastVector	getResultVector() Returns the resultVector
java.lang.String	getRevision() Returns the revision string.
SERObject	getSERObject() Returns the internal database
boolean	getShowGUI() Returns the flag for showing the OPTICS visualizer GUI.
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.
boolean	getWriteOPTICSresults() Returns the flag for writing actions
java.lang.String	globalInfo() Returns a string describing this DataMining-Algorithm
java.util.Enumeration	listOptions() Returns an enumeration of all the available options.
static void	main(java.lang.String[] args) Main Method for testing OPTICS
java.lang.String	minPointsTipText() Returns the tip text for this property
int	numberOfClusters() Returns the number of clusters.
void	setDatabase_distanceType(java.lang.String database_distanceType) Sets a new distance-type
void	setDatabase_Type(java.lang.String database_Type) Sets a new database-type
void	setDatabaseOutput(java.io.File value) Sets the the file to save the generated database to.
void	setEpsilon(double epsilon) Sets a new value for epsilon
void	setMinPoints(int minPoints) Sets a new value for minPoints
void	setOptions(java.lang.String[] options) Sets the OptionHandler's options using the given list.
void	setShowGUI(boolean value) Sets the flag for displaying the GUI.
void	setWriteOPTICSresults(boolean writeOPTICSresults) Sets the flag for writing actions
java.lang.String	showGUITipText() Returns the tip text for this property.
java.lang.String	toString() Returns a description of the clusterer
java.lang.String	writeOPTICSresultsTipText() Returns the tip text for this property

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

Constructor Detail

OPTICS

public OPTICS()

Method Detail

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 instances)
                    throws java.lang.Exception

Generate Clustering via OPTICS

Specified by:

buildClusterer in interface Clusterer

Specified by:

buildClusterer in class AbstractClusterer

Parameters:

instances - The instances that need to be clustered

Throws:

java.lang.Exception - If clustering was not successful

clusterInstance

public int clusterInstance(Instance instance)
                    throws java.lang.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:

java.lang.Exception - If instance could not be clustered successfully

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:

int The number of clusters generated for a training dataset.

Throws:

java.lang.Exception - If number of clusters could not be returned successfully

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration of all the available options.

Specified by:

listOptions in interface OptionHandler

Returns:

Enumeration 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:

 -E <double>
  epsilon (default = 0.9)

 -M <int>
  minPoints (default = 6)

 -I <String>
  index (database) used for OPTICS (default = weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase)

 -D <String>
  distance-type (default = weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject)

 -F
  write results to OPTICS_#TimeStamp#.TXT - File

 -no-gui
  suppress the display of the GUI after building the clusterer

 -db-output <file>
  The file to save the generated database to. If a directory
  is provided, the database doesn't get saved.
  The generated file can be viewed with the OPTICS Visualizer:
    java weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.OPTICS_Visualizer [file.ser]
  (default: .)

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 option settings for the OptionHandler.

Specified by:

getOptions in interface OptionHandler

Returns:

String[] The list of current option settings as an array of strings

databaseForName

public Database databaseForName(java.lang.String database_Type,
                                Instances instances)

Returns a new Class-Instance of the specified database

Parameters:

database_Type - String of the specified database

instances - Instances that were delivered from WEKA

Returns:

Database New constructed Database

dataObjectForName

public DataObject dataObjectForName(java.lang.String database_distanceType,
                                    Instance instance,
                                    java.lang.String key,
                                    Database database)

Returns a new Class-Instance of the specified database

Parameters:

database_distanceType - String of the specified distance-type

instance - The original instance that needs to hold by this DataObject

key - Key for this DataObject

database - Link to the database

Returns:

DataObject New constructed DataObject

setMinPoints

public void setMinPoints(int minPoints)

Sets a new value for minPoints

Parameters:

minPoints - MinPoints

setEpsilon

public void setEpsilon(double epsilon)

Sets a new value for epsilon

Parameters:

epsilon - Epsilon

getEpsilon

public double getEpsilon()

Returns the value of epsilon

Returns:

double Epsilon

getMinPoints

public int getMinPoints()

Returns the value of minPoints

Returns:

int MinPoints

getDatabase_distanceType

public java.lang.String getDatabase_distanceType()

Returns the distance-type

Returns:

String Distance-type

getDatabase_Type

public java.lang.String getDatabase_Type()

Returns the type of the used index (database)

Returns:

String Index-type

setDatabase_distanceType

public void setDatabase_distanceType(java.lang.String database_distanceType)

Sets a new distance-type

Parameters:

database_distanceType - The new distance-type

setDatabase_Type

public void setDatabase_Type(java.lang.String database_Type)

Sets a new database-type

Parameters:

database_Type - The new database-type

getWriteOPTICSresults

public boolean getWriteOPTICSresults()

Returns the flag for writing actions

Returns:

writeOPTICSresults (flag)

setWriteOPTICSresults

public void setWriteOPTICSresults(boolean writeOPTICSresults)

Sets the flag for writing actions

Parameters:

writeOPTICSresults - Results are written to a file if the flag is set

getShowGUI

public boolean getShowGUI()

Returns the flag for showing the OPTICS visualizer GUI.

Returns:

true if the GUI is displayed

setShowGUI

public void setShowGUI(boolean value)

Sets the flag for displaying the GUI.

Parameters:

value - if true, then the OPTICS visualizer GUI will be displayed after building the clusterer

getDatabaseOutput

public java.io.File getDatabaseOutput()

Returns the file to save the database to - if directory, database is not saved.

Returns:

the file to save the database to a directory if saving is ignored

setDatabaseOutput

public void setDatabaseOutput(java.io.File value)

Sets the the file to save the generated database to. If a directory is provided, the datbase doesn't get saved.

Parameters:

value - the file to save the database to or a directory if saving is to be ignored

getResultVector

public FastVector getResultVector()

Returns the resultVector

Returns:

resultVector

epsilonTipText

public java.lang.String epsilonTipText()

Returns the tip text for this property

Returns:

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

minPointsTipText

public java.lang.String minPointsTipText()

Returns the tip text for this property

Returns:

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

database_TypeTipText

public java.lang.String database_TypeTipText()

Returns the tip text for this property

Returns:

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

database_distanceTypeTipText

public java.lang.String database_distanceTypeTipText()

Returns the tip text for this property

Returns:

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

writeOPTICSresultsTipText

public java.lang.String writeOPTICSresultsTipText()

Returns the tip text for this property

Returns:

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

showGUITipText

public java.lang.String showGUITipText()

Returns the tip text for this property.

Returns:

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

databaseOutputTipText

public java.lang.String databaseOutputTipText()

Returns the tip text for this property.

Returns:

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

globalInfo

public java.lang.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

getSERObject

public SERObject getSERObject()

Returns the internal database

Returns:

the internal database

toString

public java.lang.String toString()

Returns a description of the clusterer

Overrides:

toString in class java.lang.Object

Returns:

the clusterer as string

getRevision

public java.lang.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(java.lang.String[] args)

Main Method for testing OPTICS

Parameters:

args - Valid parameters are: 'E' epsilon (default = 0.9); 'M' minPoints (default = 6); 'I' index-type (default = weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase); 'D' distance-type (default = weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject); 'F' write results to OPTICS_#TimeStamp#.TXT - File