Class ClassificationViaRegression

All Implemented Interfaces:
Serializable, Cloneable, 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: 1.27 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)
See Also:
  • Constructor Details

    • ClassificationViaRegression

      public ClassificationViaRegression()
      Default constructor.
  • Method Details

    • 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 CapabilitiesHandler
      Overrides:
      getCapabilities in class SingleClassifierEnhancer
      Returns:
      the capabilities of this classifier
      See Also:
    • buildClassifier

      public void buildClassifier(Instances insts) throws Exception
      Builds the classifiers.
      Specified by:
      buildClassifier in class 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.
      Overrides:
      distributionForInstance in class Classifier
      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 Classifier
      Returns:
      the revision
    • main

      public static void main(String[] argv)
      Main method for testing this class.
      Parameters:
      argv - the options for the learner