weka.classifiers.meta

Class ClassificationViaClustering

java.lang.Object

weka.classifiers.Classifier

weka.classifiers.meta.ClassificationViaClustering

All Implemented Interfaces:

Serializable, Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler

public class ClassificationViaClustering
extends Classifier

A simple meta-classifier that uses a clusterer for classification. For cluster algorithms that use a fixed number of clusterers, like SimpleKMeans, the user has to make sure that the number of clusters to generate are the same as the number of class labels in the dataset in order to obtain a useful model.

Note: at prediction time, a missing value is returned if no cluster is found for the instance.

The code is based on the 'clusters to classes' functionality of the weka.clusterers.ClusterEvaluation class by Mark Hall.

Valid options are:

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

 -W
  Full name of 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)

Version:

$Revision: 1.5 $

Author:

fracpete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ClassificationViaClustering() default constructor

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(Instances data) builds the classifier
double	classifyInstance(Instance instance) Classifies the given test instance.
String	clustererTipText() Returns the tip text for this property
Capabilities	getCapabilities() Returns default capabilities of the classifier.
Clusterer	getClusterer() Get the clusterer used as the base learner.
String[]	getOptions() returns the options of the current setup
String	getRevision() Returns the revision string.
String	globalInfo() Returns a string describing classifier
Enumeration	listOptions() Gets an enumeration describing the available options.
static void	main(String[] args) Runs the classifier with the given options
void	setClusterer(Clusterer value) Set the base clusterer.
void	setOptions(String[] options) Parses the options for this object.
String	toString() Returns a string representation of the classifier.

Methods inherited from class weka.classifiers.Classifier

debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug

Methods inherited from class java.lang.Object

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

Constructor Detail

ClassificationViaClustering

public ClassificationViaClustering()

default constructor

Method Detail

globalInfo

public String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

listOptions

public Enumeration listOptions()

Gets an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class Classifier

Returns:

an enumeration of all the available options.

getOptions

public String[] getOptions()

returns the options of the current setup

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class Classifier

Returns:

the current options

setOptions

public void setOptions(String[] options)
                throws Exception

Parses the options for this object.

Valid options are:

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

 -W
  Full name of 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 Classifier

Parameters:

options - the options to use

Throws:

Exception - if setting of options fails

clustererTipText

public String clustererTipText()

Returns the tip text for this property

Returns:

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

setClusterer

public void setClusterer(Clusterer value)

Set the base clusterer.

Parameters:

value - the clusterer to use.

getClusterer

public Clusterer getClusterer()

Get the clusterer used as the base learner.

Returns:

the current clusterer

classifyInstance

public double classifyInstance(Instance instance)
                        throws Exception

Classifies the given test instance.

Overrides:

classifyInstance in class Classifier

Parameters:

instance - the instance to be classified

Returns:

the predicted most likely class for the instance or Instance.missingValue() if no prediction is made

Throws:

Exception - if an error occurred during the prediction

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class Classifier

Returns:

the capabilities of this classifier

See Also:

Capabilities

buildClassifier

public void buildClassifier(Instances data)
                     throws Exception

builds the classifier

Specified by:

buildClassifier in class Classifier

Parameters:

data - the training instances

Throws:

Exception - if something goes wrong

toString

public String toString()

Returns a string representation of the classifier.

Overrides:

toString in class Object

Returns:

a string representation of the classifier.

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class Classifier

Returns:

the revision

main

public static void main(String[] args)

Runs the classifier with the given options

Parameters:

args - the commandline options