Package weka.classifiers.meta

Class OrdinalClassClassifier

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler
    public class OrdinalClassClassifier
extends SingleClassifierEnhancer
implements OptionHandler, TechnicalInformationHandler
    Meta classifier that allows standard classification algorithms to be applied to ordinal class problems.

    For more information see:

    Eibe Frank, Mark Hall: A Simple Approach to Ordinal Classification. In: 12th European Conference on Machine Learning, 145-156, 2001.

    BibTeX: 

     @inproceedings{Frank2001,
    author = {Eibe Frank and Mark Hall},
    booktitle = {12th European Conference on Machine Learning},
    pages = {145-156},
    publisher = {Springer},
    title = {A Simple Approach to Ordinal Classification},
    year = {2001}
 }

    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.J48)
     
 Options specific to classifier weka.classifiers.trees.J48:
 
     -U
  Use unpruned tree.
     -C <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)
     -M <minimum number of instances>
  Set minimum number of instances per leaf.
  (default 2)
     -R
  Use reduced error pruning.
     -N <number of folds>
  Set number of folds for reduced error
  pruning. One fold is used as pruning set.
  (default 3)
     -B
  Use binary splits only.
     -S
  Don't perform subtree raising.
     -L
  Do not clean up after the tree has been built.
     -A
  Laplace smoothing for predicted probabilities.
     -Q <seed>
  Seed for random data shuffling (default 1).
    Version:
    $Revision 1.0 $
    Author:
    Mark Hall
    See Also:
    OptionHandler, Serialized Form

    • Constructor Detail

      • OrdinalClassClassifier

        public OrdinalClassClassifier()
        Default constructor.

    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing this attribute evaluator
        Returns:
        a description of the evaluator 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

      • buildClassifier

        public void buildClassifier​(Instances insts)
                     throws java.lang.Exception
        Builds the classifiers.
        Specified by:
        buildClassifier in class 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.
        Overrides:
        distributionForInstance in class Classifier
        Parameters:
        inst - the instance to compute the distribution for
        Returns:
        the class distribution for the given instance
        Throws:
        java.lang.Exception - if the distribution can't be computed successfully

      • setOptions

        public void setOptions​(java.lang.String[] options)
                throws java.lang.Exception
        Parses a given list of options.

        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.J48)
         
 Options specific to classifier weka.classifiers.trees.J48:
 
         -U
  Use unpruned tree.
         -C <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)
         -M <minimum number of instances>
  Set minimum number of instances per leaf.
  (default 2)
         -R
  Use reduced error pruning.
         -N <number of folds>
  Set number of folds for reduced error
  pruning. One fold is used as pruning set.
  (default 3)
         -B
  Use binary splits only.
         -S
  Don't perform subtree raising.
         -L
  Do not clean up after the tree has been built.
         -A
  Laplace smoothing for predicted probabilities.
         -Q <seed>
  Seed for random data shuffling (default 1).
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class SingleClassifierEnhancer
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported

      • toString

        public java.lang.String toString()
        Prints the classifiers.
        Overrides:
        toString in class java.lang.Object
        Returns:
        a string representation of this classifier

      • main

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