HierarchicalClusterer (weka-stable 3.8.3 API)

java.lang.Object
- weka.clusterers.AbstractClusterer
- - weka.clusterers.HierarchicalClusterer

All Implemented Interfaces:: Serializable, 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: 13179 $
Author:: Remco Bouckaert ([email protected], [email protected]), Eibe Frank ([email protected])
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

Fields
Modifier and Type	Field and Description
`static Tag[]`	`TAGS_LINK_TYPE`

Constructor Summary

Constructors
Constructor and Description

HierarchicalClusterer()

Constructors
Constructor and Description
`HierarchicalClusterer()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildClusterer(Instances data)` Generates a clusterer.
`int`	`clusterInstance(Instance instance)` Classifies a given instance.
`String`	`distanceFunctionTipText()`
`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()`
`String[]`	`getOptions()` Gets the current settings of the clusterer.
`boolean`	`getPrintNewick()`
`String`	`getRevision()` Returns the revision string.
`String`	`globalInfo()` This will return a string describing the clusterer.
`String`	`graph()` Returns a string that describes a graph representing the object.
`int`	`graphType()` Returns the type of graph representing the object.
`String`	`linkTypeTipText()`
`Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(String[] argv)`
`int`	`numberOfClusters()` Returns the number of clusters.
`String`	`numClustersTipText()`
`String`	`printNewickTipText()`
`void`	`setDistanceFunction(DistanceFunction distanceFunction)`
`void`	`setDistanceIsBranchLength(boolean bDistanceIsHeight)`
`void`	`setLinkType(SelectedTag newLinkType)`
`void`	`setNumClusters(int nClusters)`
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setPrintNewick(boolean bPrintNewick)`
`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

- 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 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:
    
    Exception - if the clusterer has not been generated successfully
  - clusterInstance
```
public int clusterInstance(Instance instance)
                    throws 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:
    
    Exception - if instance could not be clustered successfully
  - distributionForInstance
```
public double[] distributionForInstance(Instance instance)
                                 throws 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:
    
    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 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:
    
    Exception - if number of clusters could not be returned successfully
  - listOptions
```
public 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(String[] options)
                throws 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:
    
    Exception - if an option is not supported
  - getOptions
```
public 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 String toString()
```
    Overrides:
    
    toString in class Object
  - getDistanceIsBranchLength
```
public boolean getDistanceIsBranchLength()
```
  - setDistanceIsBranchLength
```
public void setDistanceIsBranchLength(boolean bDistanceIsHeight)
```
  - distanceIsBranchLengthTipText
```
public String distanceIsBranchLengthTipText()
```
  - numClustersTipText
```
public String numClustersTipText()
```
    Returns:
    
    a string to describe the NumClusters
  - printNewickTipText
```
public String printNewickTipText()
```
    Returns:
    
    a string to describe the print Newick flag
  - distanceFunctionTipText
```
public String distanceFunctionTipText()
```
    Returns:
    
    a string to describe the distance function
  - linkTypeTipText
```
public String linkTypeTipText()
```
    Returns:
    
    a string to describe the Link type
  - globalInfo
```
public String globalInfo()
```
    This will return a string describing the clusterer.
    
    Returns:
    
    The string.
  - main
```
public static void main(String[] argv)
```
  - graph
```
public String graph()
             throws 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:
    
    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 String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class AbstractClusterer
    
    Returns:
    
    the revision

Class HierarchicalClusterer

Field Summary

Fields inherited from interface weka.core.Drawable

Constructor Summary

Method Summary

Methods inherited from class weka.clusterers.AbstractClusterer

Methods inherited from class java.lang.Object

Field Detail

TAGS_LINK_TYPE

Constructor Detail

HierarchicalClusterer

Method Detail

setNumClusters

getNumClusters

getDistanceFunction

setDistanceFunction

getPrintNewick

setPrintNewick

setLinkType

getLinkType

buildClusterer

clusterInstance

distributionForInstance

getCapabilities

numberOfClusters

listOptions

setOptions

getOptions

toString

getDistanceIsBranchLength

setDistanceIsBranchLength

distanceIsBranchLengthTipText

numClustersTipText

printNewickTipText

distanceFunctionTipText

linkTypeTipText

globalInfo

main

graph

graphType

getRevision