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Class weka.classifiers.ClassificationViaRegression

java.lang.Object
    |
    +----weka.classifiers.Classifier
            |
            +----weka.classifiers.DistributionClassifier
                    |
                    +----weka.classifiers.ClassificationViaRegression

public class ClassificationViaRegression
extends DistributionClassifier
implements OptionHandler
Class for doing classification using regression methods. For more information, see

E. Frank, Y. Wang, S. Inglis, G. Holmes, and I.H. Witten (1998) "Using model trees for classification", Machine Learning, Vol.32, No.1, pp. 63-76.

Valid options are:

-W classname
Specify the full class name of a numeric predictor as the basis for the classifier (required).

Version:
$Revision: 1.9 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)
Author:
Len Trigg (trigg@cs.waikato.ac.nz)

Constructor Index

 o ClassificationViaRegression()
 

Method Index

 o buildClassifier(Instances)
Builds the classifiers.
 o distributionForInstance(Instance)
Returns the distribution for an instance.
 o getClassifier()
Get the base classifier (regression scheme) used as the classifier
 o getOptions()
Gets the current settings of the Classifier.
 o listOptions()
Returns an enumeration describing the available options
 o main(String[])
Main method for testing this class.
 o setClassifier(Classifier)
Set the base classifier.
 o setOptions(String[])
Sets a given list of options.
 o toString()
Prints the classifiers.

Constructor Detail

 o ClassificationViaRegression
public ClassificationViaRegression()

Method Detail

 o buildClassifier
public void buildClassifier(Instances insts) throws java.lang.Exception
          Builds the classifiers.
Parameters:
insts - the training data.
Throws:
java.lang.Exception - if a classifier can't be built
Overrides:
buildClassifier in class Classifier
 o distributionForInstance
public double[] distributionForInstance(Instance inst) throws java.lang.Exception
          Returns the distribution for an instance.
Throws:
java.lang.Exception - if the distribution can't be computed successfully
Overrides:
distributionForInstance in class DistributionClassifier
 o toString
public java.lang.String toString()
          Prints the classifiers.
Overrides:
toString in class java.lang.Object
 o listOptions
public java.util.Enumeration listOptions()
          Returns an enumeration describing the available options
Returns:
an enumeration of all the available options
 o setOptions
public void setOptions(java.lang.String options[]) throws java.lang.Exception
          Sets a given list of options. Valid options are:

-W classname
Specify the full class name of a numeric predictor as the basis for the classifier (required).

Parameters:
options - the list of options as an array of strings
Throws:
java.lang.Exception - if an option is not supported
 o getOptions
public java.lang.String[] getOptions()
          Gets the current settings of the Classifier.
Returns:
an array of strings suitable for passing to setOptions
 o setClassifier
public void setClassifier(Classifier newClassifier)
          Set the base classifier.
Parameters:
newClassifier - the Classifier to use.
 o getClassifier
public Classifier getClassifier()
          Get the base classifier (regression scheme) used as the classifier
Returns:
the classifier used as the classifier
 o 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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