weka.classifiers.meta

Class ClassificationViaRegression

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

weka.classifiers.meta.ClassificationViaRegression

All Implemented Interfaces:

Serializable, Cloneable, Classifier, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class ClassificationViaRegression
extends SingleClassifierEnhancer
implements TechnicalInformationHandler

Class for doing classification using regression methods. Class is binarized and one regression model is built for each class value. For more information, see, for example

E. Frank, Y. Wang, S. Inglis, G. Holmes, I.H. Witten (1998). Using model trees for classification. Machine Learning. 32(1):63-76.

BibTeX:

 @article{Frank1998,
    author = {E. Frank and Y. Wang and S. Inglis and G. Holmes and I.H. Witten},
    journal = {Machine Learning},
    number = {1},
    pages = {63-76},
    title = {Using model trees for classification},
    volume = {32},
    year = {1998}
 }
 

Valid options are:

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

 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.M5P)

 
 Options specific to classifier weka.classifiers.trees.M5P:
 

 -N
  Use unpruned tree/rules

 -U
  Use unsmoothed predictions

 -R
  Build regression tree/rule rather than a model tree/rule

 -M <minimum number of instances>
  Set minimum number of instances per leaf
  (default 4)

 -L
  Save instances at the nodes in
  the tree (for visualization purposes)

Version:

$Revision: 8034 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ClassificationViaRegression() Default constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	buildClassifier(Instances insts) Builds the classifiers.
double[]	distributionForInstance(Instance inst) Returns the distribution for an instance.
Capabilities	getCapabilities() Returns default capabilities of the classifier.
String	getRevision() Returns the revision string.
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.
String	globalInfo() Returns a string describing classifier
static void	main(String[] argv) Main method for testing this class.
String	toString() Prints the classifiers.

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier, getOptions, listOptions, setClassifier, setOptions

Methods inherited from class weka.classifiers.AbstractClassifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug

Methods inherited from class java.lang.Object

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

Constructor Detail

ClassificationViaRegression

public ClassificationViaRegression()

Default constructor.

Method Detail

globalInfo

public String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

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

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface Classifier

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class SingleClassifierEnhancer

Returns:

the capabilities of this classifier

See Also:

Capabilities

buildClassifier

public void buildClassifier(Instances insts)
                     throws Exception

Builds the classifiers.

Specified by:

buildClassifier in interface Classifier

Parameters:

insts - the training data.

Throws:

Exception - if a classifier can't be built

distributionForInstance

public double[] distributionForInstance(Instance inst)
                                 throws Exception

Returns the distribution for an instance.

Specified by:

distributionForInstance in interface Classifier

Overrides:

distributionForInstance in class AbstractClassifier

Parameters:

inst - the instance to get the distribution for

Returns:

the computed distribution

Throws:

Exception - if the distribution can't be computed successfully

toString

public String toString()

Prints the classifiers.

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 AbstractClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - the options for the learner