weka.classifiers.trees

Class NBTree

java.lang.Object

weka.classifiers.Classifier

weka.classifiers.trees.NBTree

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, Drawable, OptionHandler, RevisionHandler, Summarizable, TechnicalInformationHandler, WeightedInstancesHandler

public class NBTree
extends Classifier
implements WeightedInstancesHandler, Drawable, Summarizable, AdditionalMeasureProducer, TechnicalInformationHandler

Class for generating a decision tree with naive Bayes classifiers at the leaves.

For more information, see

Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996.

BibTeX:

 @inproceedings{Kohavi1996,
    author = {Ron Kohavi},
    booktitle = {Second International Conference on Knoledge Discovery and Data Mining},
    pages = {202-207},
    title = {Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid},
    year = {1996}
 }
 

Valid options are:

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Version:

$Revision: 1.10 $

Author:

Mark Hall

See Also:

Serialized Form

Field Summary

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors

Constructor and Description
NBTree()

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(Instances instances) Generates the classifier.
double	classifyInstance(Instance instance) Classifies an instance.
double[]	distributionForInstance(Instance instance) Returns class probabilities for an instance.
java.util.Enumeration	enumerateMeasures() Returns an enumeration of the additional measure names
Capabilities	getCapabilities() Returns default capabilities of the classifier.
double	getMeasure(java.lang.String additionalMeasureName) Returns the value of the named measure
java.lang.String	getRevision() Returns the revision string.
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.
java.lang.String	globalInfo() Returns a string describing classifier
java.lang.String	graph() Returns graph describing the tree.
int	graphType() Returns the type of graph this classifier represents.
static void	main(java.lang.String[] argv) Main method for testing this class
double	measureNumLeaves() Returns the number of leaves
double	measureNumRules() Returns the number of rules (same as number of leaves)
double	measureTreeSize() Returns the size of the tree
java.lang.String	toString() Returns a description of the classifier.
java.lang.String	toSummaryString() Returns a superconcise version of the model

Methods inherited from class weka.classifiers.Classifier

debugTipText, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

NBTree

public NBTree()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Returns:

a description 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

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class Classifier

Returns:

the capabilities of this classifier

See Also:

Capabilities

buildClassifier

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

Generates the classifier.

Specified by:

buildClassifier in class Classifier

Parameters:

instances - the data to train with

Throws:

java.lang.Exception - if classifier can't be built successfully

classifyInstance

public double classifyInstance(Instance instance)
                        throws java.lang.Exception

Classifies an instance.

Overrides:

classifyInstance in class Classifier

Parameters:

instance - the instance to classify

Returns:

the classification

Throws:

java.lang.Exception - if instance can't be classified successfully

distributionForInstance

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

Returns class probabilities for an instance.

Overrides:

distributionForInstance in class Classifier

Parameters:

instance - the instance to get the distribution for

Returns:

the class probabilities

Throws:

java.lang.Exception - if distribution can't be computed successfully

toString

public java.lang.String toString()

Returns a description of the classifier.

Overrides:

toString in class java.lang.Object

Returns:

a string representation of the classifier

graphType

public int graphType()

Returns the type of graph this classifier represents.

Specified by:

graphType in interface Drawable

Returns:

Drawable.TREE

graph

public java.lang.String graph()
                       throws java.lang.Exception

Returns graph describing the tree.

Specified by:

graph in interface Drawable

Returns:

the graph describing the tree

Throws:

java.lang.Exception - if graph can't be computed

toSummaryString

public java.lang.String toSummaryString()

Returns a superconcise version of the model

Specified by:

toSummaryString in interface Summarizable

Returns:

a description of the model

measureTreeSize

public double measureTreeSize()

Returns the size of the tree

Returns:

the size of the tree

measureNumLeaves

public double measureNumLeaves()

Returns the number of leaves

Returns:

the number of leaves

measureNumRules

public double measureNumRules()

Returns the number of rules (same as number of leaves)

Returns:

the number of rules

getMeasure

public double getMeasure(java.lang.String additionalMeasureName)

Returns the value of the named measure

Specified by:

getMeasure in interface AdditionalMeasureProducer

Parameters:

additionalMeasureName - the name of the measure to query for its value

Returns:

the value of the named measure

Throws:

java.lang.IllegalArgumentException - if the named measure is not supported

enumerateMeasures

public java.util.Enumeration enumerateMeasures()

Returns an enumeration of the additional measure names

Specified by:

enumerateMeasures in interface AdditionalMeasureProducer

Returns:

an enumeration of the measure names

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class Classifier

Returns:

the revision

main

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

Main method for testing this class

Parameters:

argv - the commandline options