weka.classifiers.meta
Class Grading

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.MultipleClassifiersCombiner
              |
              +--weka.classifiers.RandomizableMultipleClassifiersCombiner
                    |
                    +--weka.classifiers.meta.Stacking
                          |
                          +--weka.classifiers.meta.Grading
All Implemented Interfaces:
java.lang.Cloneable, OptionHandler, Randomizable, java.io.Serializable

public class Grading
extends Stacking

Implements Grading. For more information, see

Seewald A.K., Fuernkranz J. (2001): An Evaluation of Grading Classifiers, in Hoffmann F.\ et al.\ (eds.), Advances in Intelligent Data Analysis, 4th International Conference, IDA 2001, Proceedings, Springer, Berlin/Heidelberg/New York/Tokyo, pp.115-124, 2001 Valid options are:

-X num_folds
The number of folds for the cross-validation (default 10).

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a base scheme followed by options to the classifier. (required, option should be used once for each classifier).

-M classifierstring
Classifierstring for the meta classifier. Same format as for base classifiers. This classifier estimates confidence in prediction of base classifiers. (required)

Version:
$Revision: 1.4 $
Author:
Alexander K. Seewald (alex@seewald.at), Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
Serialized Form

Constructor Summary
Grading()
           
 
Method Summary
 double[] distributionForInstance(Instance instance)
          Returns class probabilities for a given instance using the stacked classifier.
 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()
          Output a representation of this classifier
 
Methods inherited from class weka.classifiers.meta.Stacking
buildClassifier, getMetaClassifier, getNumFolds, getOptions, listOptions, metaClassifierTipText, numFoldsTipText, setMetaClassifier, setNumFolds, setOptions
 
Methods inherited from class weka.classifiers.RandomizableMultipleClassifiersCombiner
getSeed, seedTipText, setSeed
 
Methods inherited from class weka.classifiers.MultipleClassifiersCombiner
classifiersTipText, getClassifier, getClassifiers, setClassifiers
 
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

Grading

public Grading()
Method Detail

globalInfo

public java.lang.String globalInfo()
Returns a string describing classifier

Overrides:
globalInfo in class Stacking
Returns:
a description suitable for displaying in the explorer/experimenter gui

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception
Returns class probabilities for a given instance using the stacked classifier. One class will always get all the probability mass (i.e. probability one).

Overrides:
distributionForInstance in class Stacking
Parameters:
instance - the instance to be classified
Throws:
java.lang.Exception - if instance could not be classified successfully

toString

public java.lang.String toString()
Output a representation of this classifier

Overrides:
toString in class Stacking

main

public static void main(java.lang.String[] argv)
Main method for testing this class.

Parameters:
argv - should contain the following arguments: -t training file [-T test file] [-c class index]


Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London