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## weka.classifiers.meta
Class ClassificationViaRegression

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

All Implemented Interfaces:
  java.io.Serializable, java.lang.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: 5928 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`ClassificationViaRegression()` Default constructor.

Method Summary
`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.
`java.lang.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.
`java.lang.String` | `globalInfo()` Returns a string describing classifier
`static void` | `main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.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, 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 java.lang.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 java.lang.Exception

  Builds the classifiers.

  Specified by:
    `buildClassifier` in interface `Classifier`
  Parameters:
    `insts` - the training data.
  Throws:
    `java.lang.Exception` - if a classifier can't be built

### distributionForInstance

    public double[] distributionForInstance(Instance inst)
                                     throws java.lang.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:
    `java.lang.Exception` - if the distribution can't be computed successfully

### toString

    public java.lang.String toString()

  Prints the classifiers.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a string representation of the classifier

### getRevision

    public java.lang.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(java.lang.String[] argv)

  Main method for testing this class.

  Parameters:
    `argv` - the options for the learner

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