weka.classifiers.rules
Class ZeroR

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.rules.ZeroR
All Implemented Interfaces:
java.lang.Cloneable, OptionHandler, java.io.Serializable, WeightedInstancesHandler

public class ZeroR
extends Classifier
implements WeightedInstancesHandler

Class for building and using a 0-R classifier. Predicts the mean (for a numeric class) or the mode (for a nominal class).

Version:
$Revision: 1.10 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
Serialized Form

Constructor Summary
ZeroR()
           
 
Method Summary
 void buildClassifier(Instances instances)
          Generates the classifier.
 double classifyInstance(Instance instance)
          Classifies a given instance.
 double[] distributionForInstance(Instance instance)
          Calculates the class membership probabilities for the given test instance.
 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()
          Returns a description of the classifier.
 
Methods inherited from class weka.classifiers.Classifier
debugTipText, forName, getDebug, getOptions, listOptions, makeCopies, setDebug, setOptions
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

ZeroR

public ZeroR()
Method Detail

globalInfo

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

Returns:
a description suitable for displaying in the explorer/experimenter gui

buildClassifier

public void buildClassifier(Instances instances)
                     throws java.lang.Exception
Generates the classifier.

Specified by:
buildClassifier in class Classifier
Parameters:
instances - set of instances serving as training data
Throws:
java.lang.Exception - if the classifier has not been generated successfully

classifyInstance

public double classifyInstance(Instance instance)
Classifies a given instance.

Overrides:
classifyInstance in class Classifier
Parameters:
instance - the instance to be classified
Returns:
index of the predicted class

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception
Calculates the class membership probabilities for the given test instance.

Overrides:
distributionForInstance in class Classifier
Parameters:
instance - the instance to be classified
Returns:
predicted class probability distribution
Throws:
java.lang.Exception - if class is numeric

toString

public java.lang.String toString()
Returns a description of the classifier.

Overrides:
toString in class java.lang.Object
Returns:
a description of the classifier as a string.

main

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

Parameters:
argv - the options


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