weka.classifiers.meta
Class ND

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.meta.ND

All Implemented Interfaces:

java.lang.Cloneable, NestedDichotomy, OptionHandler, Randomizable, java.io.Serializable

public class ND

extends Classifier

implements NestedDichotomy, OptionHandler

See Also:

Serialized Form

Nested Class Summary

protected class

ND.NDTree

Field Summary

protected Classifier	m_classifier The base classifier .
protected java.util.Hashtable	m_classifiers The hashtable containing all the classifiers
protected boolean	m_hashtablegiven Is Hashtable given from END?
protected ND.NDTree	m_ndtree The tree of classes
protected int	m_seed The random number seed used

Fields inherited from class weka.classifiers.Classifier

m_Debug

Constructor Summary

ND()

Method Summary

void	buildClassifier(Instances data) Builds the classifier.
void	buildClassifierForNode(ND.NDTree node, Instances data) Builds the classifier for one node.
double[]	distributionForInstance(Instance inst) Predicts the class distribution for a given instance
protected double[]	distributionForInstance(Instance inst, ND.NDTree node) Predicts the class distribution for a given instance
Classifier	getClassifier() Get the classifier used as the classifier
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
int	getSeed() Gets the random number seed.
java.util.Enumeration	listOptions() Returns an enumeration describing the available options
static void	main(java.lang.String[] argv) Main method for testing this class.
void	setClassifier(Classifier newClassifier) Set the base classifier.
void	setHashtable(java.util.Hashtable table) Set hashtable from END.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setSeed(int seed) Sets the seed for random number generation.
java.lang.String	toString() Outputs the classifier as a string.

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_ndtree

protected ND.NDTree m_ndtree

The tree of classes

m_classifiers

protected java.util.Hashtable m_classifiers

The hashtable containing all the classifiers

m_seed

protected int m_seed

The random number seed used

m_classifier

protected Classifier m_classifier

The base classifier .

m_hashtablegiven

protected boolean m_hashtablegiven

Is Hashtable given from END?

Constructor Detail

ND

public ND()

Method Detail

setHashtable

public void setHashtable(java.util.Hashtable table)

Set hashtable from END.

buildClassifier

public void buildClassifier(Instances data)
                     throws java.lang.Exception

Builds the classifier.

Specified by:

buildClassifier in class Classifier

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if the classifier has not been generated successfully

buildClassifierForNode

public void buildClassifierForNode(ND.NDTree node,
                                   Instances data)
                            throws java.lang.Exception

Builds the classifier for one node.

Throws:

java.lang.Exception

distributionForInstance

public double[] distributionForInstance(Instance inst)
                                 throws java.lang.Exception

Predicts the class distribution for a given instance

Overrides:

distributionForInstance in class Classifier

Parameters:

inst - the (multi-class) instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction

Throws:

java.lang.Exception - if distribution could not be computed successfully

distributionForInstance

protected double[] distributionForInstance(Instance inst,
                                           ND.NDTree node)
                                    throws java.lang.Exception

Predicts the class distribution for a given instance

Parameters:

inst - the (multi-class) instance to be classified

Throws:

java.lang.Exception

setSeed

public void setSeed(int seed)

Sets the seed for random number generation.

Specified by:

setSeed in interface Randomizable

Parameters:

seed - the random number seed

getSeed

public int getSeed()

Gets the random number seed.

Specified by:

getSeed in interface Randomizable

Returns:

the random number seed

setClassifier

public void setClassifier(Classifier newClassifier)

Set the base classifier.

Parameters:

newClassifier - the Classifier to use.

getClassifier

public Classifier getClassifier()

Get the classifier used as the classifier

Returns:

the classifier used as the classifier

toString

public java.lang.String toString()

Outputs the classifier as a string.

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class Classifier

Returns:

an enumeration of all the available options

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options. Valid options are:

-W classname
Specify the full class name of a learner as the basis for the multiclassclassifier (required).

-Q seed
Random number seed (default 1).

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class Classifier

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the Classifier.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class Classifier

Returns:

an array of strings suitable for passing to setOptions

main

public static void main(java.lang.String[] argv)

Main method for testing this class.

Parameters:

argv - the options