weka.classifiers.meta
Class ClassificationViaRegressionD

java.lang.Object
  weka.classifiers.AbstractClassifier
      weka.classifiers.SingleClassifierEnhancer
          weka.classifiers.meta.ClassificationViaRegressionD

All Implemented Interfaces:

Serializable, Cloneable, weka.classifiers.Classifier, weka.core.CapabilitiesHandler, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler

public class ClassificationViaRegressionD
extends weka.classifiers.SingleClassifierEnhancer
implements weka.core.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: 4521 $

Author:

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

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.SingleClassifierEnhancer

m_Classifier

Fields inherited from class weka.classifiers.AbstractClassifier

m_Debug

Constructor Summary

ClassificationViaRegressionD()
Default constructor.

Method Summary

void	buildClassifier(weka.core.Instances insts) Builds the classifiers.
protected String	defaultClassifierString() String describing default classifier.
double[]	distributionForInstance(weka.core.Instance inst) Returns the distribution for an instance.
weka.core.Capabilities	getCapabilities() Returns default capabilities of the classifier.
String	getRevision() Returns the revision string.
weka.core.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, getClassifierSpec, 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

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

ClassificationViaRegressionD

public ClassificationViaRegressionD()

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 weka.core.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 weka.core.TechnicalInformationHandler

Returns:

the technical information about this class

defaultClassifierString

protected String defaultClassifierString()

String describing default classifier.

Overrides:

defaultClassifierString in class weka.classifiers.SingleClassifierEnhancer

Returns:

the default classifier classname

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.classifiers.SingleClassifierEnhancer

Returns:

the capabilities of this classifier

buildClassifier

public void buildClassifier(weka.core.Instances insts)
                     throws Exception

Builds the classifiers.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

insts - the training data.

Throws:

Exception - if a classifier can't be built

distributionForInstance

public double[] distributionForInstance(weka.core.Instance inst)
                                 throws Exception

Returns the distribution for an instance.

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class weka.classifiers.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 weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - the options for the learner