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weka.clusterers
Class OPTICS

java.lang.Object
  extended by weka.clusterers.AbstractClusterer
      extended by 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

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

Version:
$Revision: 1.8 $
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
OPTICS()
           
 
Method Summary
 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
 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)
 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
 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 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 setWriteOPTICSresults(boolean writeOPTICSresults)
          Sets the flag for writing actions
 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.EuclidianDataObject)
 -F
  write results to OPTICS_#TimeStamp#.TXT - File

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

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

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
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.EuclidianDataObject); 'F' write results to OPTICS_#TimeStamp#.TXT - File
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