Package weka.clusterers

Class FilteredClusterer

java.lang.Object

weka.clusterers.AbstractClusterer

weka.clusterers.SingleClustererEnhancer

weka.clusterers.FilteredClusterer

All Implemented Interfaces:

Serializable, Cloneable, Clusterer, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, Drawable, OptionHandler, RevisionHandler

public class FilteredClusterer
extends SingleClustererEnhancer
implements Drawable

Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter. Like the clusterer, the structure of the filter is based exclusively on the training data and test instances will be processed by the filter without changing their structure.

Valid options are:

 -F <filter specification>
  Full class name of filter to use, followed
  by filter options.
  eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
 (default: weka.filters.AllFilter)
 

 -W
  Full name of base clusterer.
  (default: weka.clusterers.SimpleKMeans)
 

 Options specific to clusterer weka.clusterers.SimpleKMeans:
 

 -N <num>
  number of clusters.
  (default 2).
 

 -V
  Display std. deviations for centroids.
 

 -M
  Replace missing values with mean/mode.
 

 -S <num>
  Random number seed.
  (default 10)
 

Based on code from the FilteredClassifier by Len Trigg.

Version:

$Revision$

Author:

Len Trigg (trigg@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)

See Also:

FilteredClassifier, Serialized Form

Field Summary

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors

Constructor	Description
FilteredClusterer()	Default constructor.

Method Summary

Modifier and Type	Method	Description
void	buildClusterer(Instances data)	Build the clusterer on the filtered data.
double[]	distributionForInstance(Instance instance)	Classifies a given instance after filtering.
String	filterTipText()	Returns the tip text for this property.
Capabilities	getCapabilities()	Returns default capabilities of the clusterer.
Filter	getFilter()	Gets the filter used.
String[]	getOptions()	Gets the current settings of the clusterer.
String	getRevision()	Returns the revision string.
String	globalInfo()	Returns a string describing this clusterer.
String	graph()	Returns graph describing the clusterer (if possible).
int	graphType()	Returns the type of graph this clusterer represents.
Enumeration<Option>	listOptions()	Returns an enumeration describing the available options.
static void	main(String[] args)	Main method for testing this class.
void	setFilter(Filter filter)	Sets the filter.
void	setOptions(String[] options)	Parses a given list of options.
String	toString()	Output a representation of this clusterer.

Methods inherited from class weka.clusterers.SingleClustererEnhancer

clustererTipText, getClusterer, numberOfClusters, setClusterer

Methods inherited from class weka.clusterers.AbstractClusterer

clusterInstance, 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

Constructor Detail

FilteredClusterer

public FilteredClusterer()

Default constructor.

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this clusterer.

Returns:

a description of the clusterer suitable for displaying in the explorer/experimenter gui

listOptions

public Enumeration<Option> listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class SingleClustererEnhancer

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:

 -F <filter specification>
  Full class name of filter to use, followed
  by filter options.
  eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
 (default: weka.filters.AllFilter)
 

 -W
  Full name of base clusterer.
  (default: weka.clusterers.SimpleKMeans)
 

 Options specific to clusterer weka.clusterers.SimpleKMeans:
 

 -N <num>
  number of clusters.
  (default 2).
 

 -V
  Display std. deviations for centroids.
 

 -M
  Replace missing values with mean/mode.
 

 -S <num>
  Random number seed.
  (default 10)
 

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class SingleClustererEnhancer

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 SingleClustererEnhancer

Returns:

an array of strings suitable for passing to setOptions

filterTipText

public String filterTipText()

Returns the tip text for this property.

Returns:

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

setFilter

public void setFilter(Filter filter)

Sets the filter.

Parameters:

filter - the filter with all options set.

getFilter

public Filter getFilter()

Gets the filter used.

Returns:

the filter

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the clusterer.

Specified by:

getCapabilities in interface CapabilitiesHandler

Specified by:

getCapabilities in interface Clusterer

Overrides:

getCapabilities in class SingleClustererEnhancer

Returns:

the capabilities of this clusterer

See Also:

Capabilities

buildClusterer

public void buildClusterer(Instances data)
                    throws Exception

Build the clusterer on the filtered data.

Specified by:

buildClusterer in interface Clusterer

Specified by:

buildClusterer in class AbstractClusterer

Parameters:

data - the training data

Throws:

Exception - if the clusterer could not be built successfully

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws Exception

Classifies a given instance after filtering.

Specified by:

distributionForInstance in interface Clusterer

Overrides:

distributionForInstance in class AbstractClusterer

Parameters:

instance - the instance to be classified

Returns:

the class distribution for the given instance

Throws:

Exception - if instance could not be classified successfully

toString

public String toString()

Output a representation of this clusterer.

Overrides:

toString in class Object

Returns:

a representation of this clusterer

graphType

public int graphType()

Returns the type of graph this clusterer represents.

Specified by:

graphType in interface Drawable

Returns:

the graph type of this clusterer

graph

public String graph()
             throws Exception

Returns graph describing the clusterer (if possible).

Specified by:

graph in interface Drawable

Returns:

the graph of the clusterer in dotty format

Throws:

Exception - if the clusterer cannot be graphed

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[] args)

Main method for testing this class.

Parameters:

args - the commandline options, use "-h" for help