weka.classifiers.bayes
Class DMNBtext

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.bayes.DMNBtext

All Implemented Interfaces:

Serializable, Cloneable, UpdateableClassifier, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

public class DMNBtext
extends Classifier
implements OptionHandler, WeightedInstancesHandler, TechnicalInformationHandler, UpdateableClassifier

Class for building and using a Discriminative Multinomial Naive Bayes classifier. For more information see,

Jiang Su,Harry Zhang,Charles X. Ling,Stan Matwin: Discriminative Parameter Learning for Bayesian Networks. In: ICML 2008', 2008.

The core equation for this classifier:

P[Ci|D] = (P[D|Ci] x P[Ci]) / P[D] (Bayes rule)

where Ci is class i and D is a document.

BibTeX:

 @inproceedings{JiangSu2008,
    author = {Jiang Su,Harry Zhang,Charles X. Ling,Stan Matwin},
    booktitle = {ICML 2008'},
    title = {Discriminative Parameter Learning for Bayesian Networks},
    year = {2008}
 }
 

Valid options are:

 -I <iterations>
  The number of iterations that the classifier 
  will scan the training data (default = 1)

 -M
  Use the frequency information in data

Version:

$Revision: 6363 $

Author:

Jiang Su (Jiang.Su@unb.ca) 2008

See Also:

Serialized Form

Nested Class Summary

class

DMNBtext.DNBBinary

Constructor Summary

DMNBtext()

Method Summary

void	buildClassifier(Instances data) Generates the classifier.
double[]	distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance.
Capabilities	getCapabilities() Returns default capabilities of the classifier.
boolean	getMultinomialWord() Gets whether use binary text representation
int	getNumIterations() Gets the number of iterations to be performed
String[]	getOptions() Gets the current settings of the classifier.
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.
String	globalInfo() Returns a string describing this classifier
Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	main(String[] argv) Main method for testing this class.
String	multinomialWordTipText() Returns the tip text for this property
String	numIterationsTipText() Returns the tip text for this property
void	setMultinomialWord(boolean val) Sets whether use binary text representation
void	setNumIterations(int numIterations) Sets the number of iterations to be performed
void	setOptions(String[] options) Parses a given list of options.
String	toString() Returns a string representation of the classifier.
void	updateClassifier(Instance instance) Updates the classifier with the given instance.

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug

Methods inherited from class java.lang.Object

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

Constructor Detail

DMNBtext

public DMNBtext()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this classifier

Returns:

a description of the classifier 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 data)
                     throws Exception

Generates the classifier.

Specified by:

buildClassifier in class Classifier

Parameters:

instances - set of instances serving as training data

Throws:

Exception - if the classifier has not been generated successfully

updateClassifier

public void updateClassifier(Instance instance)
                      throws Exception

Updates the classifier with the given instance.

Specified by:

updateClassifier in interface UpdateableClassifier

Parameters:

instance - the new training instance to include in the model

Throws:

Exception - if the instance could not be incorporated in the model.

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws 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:

Exception - if there is a problem generating the prediction

toString

public String toString()

Returns a string representation of the classifier.

Overrides:

toString in class Object

Returns:

a string representation of the classifier

listOptions

public Enumeration<Option> 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(String[] options)
                throws Exception

Description copied from class: Classifier

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.

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class Classifier

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

public 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

numIterationsTipText

public String numIterationsTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setNumIterations

public void setNumIterations(int numIterations)

Sets the number of iterations to be performed

getNumIterations

public int getNumIterations()

Gets the number of iterations to be performed

Returns:

the iterations to be performed

multinomialWordTipText

public String multinomialWordTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setMultinomialWord

public void setMultinomialWord(boolean val)

Sets whether use binary text representation

getMultinomialWord

public boolean getMultinomialWord()

Gets whether use binary text representation

Returns:

whether use binary text representation

getRevision

public 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(String[] argv)

Main method for testing this class.

Parameters:

argv - the options