weka.clusterers

Class HierarchicalClusterer

java.lang.Object

weka.clusterers.AbstractClusterer

weka.clusterers.HierarchicalClusterer

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Clusterer, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, Drawable, OptionHandler, RevisionHandler

public class HierarchicalClusterer
extends AbstractClusterer
implements OptionHandler, Drawable

Hierarchical clustering class. Implements a number of classic hierarchical clustering methods. Valid options are:

 -N
  number of clusters
 

 -L
  Link type (Single, Complete, Average, Mean, Centroid, Ward, Adjusted complete, Neighbor Joining)
  [SINGLE|COMPLETE|AVERAGE|MEAN|CENTROID|WARD|ADJCOMPLETE|NEIGHBOR_JOINING]
 

 -A
 Distance function to use. (default: weka.core.EuclideanDistance)
 

 -P
 Print hierarchy in Newick format, which can be used for display in other programs.
 

 -D
 If set, classifier is run in debug mode and may output additional info to the console.
 

 -B
 \If set, distance is interpreted as branch length, otherwise it is node height.
 

Version:

$Revision: 15519 $

Author:

Remco Bouckaert (rrb@xm.co.nz, remco@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static Tag[]	TAGS_LINK_TYPE

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors

Constructor and Description
HierarchicalClusterer()

Method Summary

Modifier and Type	Method and Description
void	buildClusterer(Instances data) Generates a clusterer.
int	clusterInstance(Instance instance) Classifies a given instance.
java.lang.String	distanceFunctionTipText()
java.lang.String	distanceIsBranchLengthTipText()
double[]	distributionForInstance(Instance instance) Predicts the cluster memberships for a given instance.
Capabilities	getCapabilities() Returns the Capabilities of this clusterer.
DistanceFunction	getDistanceFunction()
boolean	getDistanceIsBranchLength()
SelectedTag	getLinkType()
int	getNumClusters()
java.lang.String[]	getOptions() Gets the current settings of the clusterer.
boolean	getPrintNewick()
java.lang.String	getRevision() Returns the revision string.
java.lang.String	globalInfo() This will return a string describing the clusterer.
java.lang.String	graph() Returns a string that describes a graph representing the object.
int	graphType() Returns the type of graph representing the object.
java.lang.String	linkTypeTipText()
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	main(java.lang.String[] argv)
int	numberOfClusters() Returns the number of clusters.
java.lang.String	numClustersTipText()
java.lang.String	printNewickTipText()
void	setDistanceFunction(DistanceFunction distanceFunction)
void	setDistanceIsBranchLength(boolean bDistanceIsHeight)
void	setLinkType(SelectedTag newLinkType)
void	setNumClusters(int nClusters)
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setPrintNewick(boolean bPrintNewick)
java.lang.String	toString()

Methods inherited from class weka.clusterers.AbstractClusterer

debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, makeCopies, makeCopy, postExecution, preExecution, run, runClusterer, setDebug, setDoNotCheckCapabilities

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Field Detail

TAGS_LINK_TYPE

public static final Tag[] TAGS_LINK_TYPE

Constructor Detail

HierarchicalClusterer

public HierarchicalClusterer()

Method Detail

setNumClusters

public void setNumClusters(int nClusters)

getNumClusters

public int getNumClusters()

getDistanceFunction

public DistanceFunction getDistanceFunction()

setDistanceFunction

public void setDistanceFunction(DistanceFunction distanceFunction)

getPrintNewick

public boolean getPrintNewick()

setPrintNewick

public void setPrintNewick(boolean bPrintNewick)

setLinkType

public void setLinkType(SelectedTag newLinkType)

getLinkType

public SelectedTag getLinkType()

buildClusterer

public void buildClusterer(Instances data)
                    throws java.lang.Exception

Description copied from class: AbstractClusterer

Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via options.

Specified by:

buildClusterer in interface Clusterer

Specified by:

buildClusterer in class AbstractClusterer

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if the clusterer has not been generated successfully

clusterInstance

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

Description copied from class: AbstractClusterer

Classifies a given instance. Either this or distributionForInstance() needs to be implemented by subclasses.

Specified by:

clusterInstance in interface Clusterer

Overrides:

clusterInstance in class AbstractClusterer

Parameters:

instance - the instance to be assigned to a cluster

Returns:

the number of the assigned cluster as an integer

Throws:

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

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception

Description copied from class: AbstractClusterer

Predicts the cluster memberships for a given instance. Either this or clusterInstance() needs to be implemented by subclasses.

Specified by:

distributionForInstance in interface Clusterer

Overrides:

distributionForInstance in class AbstractClusterer

Parameters:

instance - the instance to be assigned a cluster.

Returns:

an array containing the estimated membership probabilities of the test instance in each cluster (this should sum to at most 1)

Throws:

java.lang.Exception - if distribution could not be computed successfully

getCapabilities

public Capabilities getCapabilities()

Description copied from class: AbstractClusterer

Returns the Capabilities of this clusterer. Derived clusterers have to override this method to enable capabilities.

Specified by:

getCapabilities in interface Clusterer

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class AbstractClusterer

Returns:

the capabilities of this object

See Also:

Capabilities

numberOfClusters

public int numberOfClusters()
                     throws java.lang.Exception

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.

Throws:

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

listOptions

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

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class AbstractClusterer

Returns:

an enumeration of all the available options.

setOptions

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

Parses a given list of options.

Valid options are:

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class AbstractClusterer

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 settings of the clusterer.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class AbstractClusterer

Returns:

an array of strings suitable for passing to setOptions()

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

getDistanceIsBranchLength

public boolean getDistanceIsBranchLength()

setDistanceIsBranchLength

public void setDistanceIsBranchLength(boolean bDistanceIsHeight)

distanceIsBranchLengthTipText

public java.lang.String distanceIsBranchLengthTipText()

numClustersTipText

public java.lang.String numClustersTipText()

Returns:

a string to describe the NumClusters

printNewickTipText

public java.lang.String printNewickTipText()

Returns:

a string to describe the print Newick flag

distanceFunctionTipText

public java.lang.String distanceFunctionTipText()

Returns:

a string to describe the distance function

linkTypeTipText

public java.lang.String linkTypeTipText()

Returns:

a string to describe the Link type

globalInfo

public java.lang.String globalInfo()

This will return a string describing the clusterer.

Returns:

The string.

main

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

graph

public java.lang.String graph()
                       throws java.lang.Exception

Description copied from interface: Drawable

Returns a string that describes a graph representing the object. The string should be in XMLBIF ver. 0.3 format if the graph is a BayesNet, otherwise it should be in dotty format.

Specified by:

graph in interface Drawable

Returns:

the graph described by a string

Throws:

java.lang.Exception - if the graph can't be computed

graphType

public int graphType()

Description copied from interface: Drawable

Returns the type of graph representing the object.

Specified by:

graphType in interface Drawable

Returns:

the type of graph representing the object

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClusterer

Returns:

the revision