weka.classifiers.bayes.net.estimate
Class BayesNetEstimator

java.lang.Object
  weka.classifiers.bayes.net.estimate.BayesNetEstimator

All Implemented Interfaces:

java.io.Serializable, OptionHandler, RevisionHandler

Direct Known Subclasses:

MultiNomialBMAEstimator, SimpleEstimator

public class BayesNetEstimator
extends java.lang.Object
implements OptionHandler, java.io.Serializable, RevisionHandler

BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has been learned.

Valid options are:

 -A <alpha>
  Initial count (alpha)
 

Version:

$Revision: 1.4 $

Author:

Remco Bouckaert ([email protected])

See Also:

Serialized Form

Constructor Summary

BayesNetEstimator()

Method Summary

java.lang.String	alphaTipText()
double[]	distributionForInstance(BayesNet bayesNet, Instance instance) Calculates the class membership probabilities for the given test instance.
void	estimateCPTs(BayesNet bayesNet) estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
double	getAlpha() Get prior used in probability table estimation
java.lang.String[]	getOptions() Gets the current settings of the classifier.
java.lang.String	getRevision() Returns the revision string.
java.lang.String	globalInfo() This will return a string describing the class.
void	initCPTs(BayesNet bayesNet) initCPTs reserves space for CPTs and set all counts to zero
java.util.Enumeration	listOptions() Returns an enumeration describing the available options
void	setAlpha(double fAlpha) Set prior used in probability table estimation
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	updateClassifier(BayesNet bayesNet, Instance instance) Updates the classifier with the given instance.

Methods inherited from class java.lang.Object

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

Constructor Detail

BayesNetEstimator

public BayesNetEstimator()

Method Detail

estimateCPTs

public void estimateCPTs(BayesNet bayesNet)
                  throws java.lang.Exception

estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.

Parameters:

bayesNet - the bayes net to use

Throws:

java.lang.Exception - always throws an exception, since subclass needs to be used

updateClassifier

public void updateClassifier(BayesNet bayesNet,
                             Instance instance)
                      throws java.lang.Exception

Updates the classifier with the given instance.

Parameters:

bayesNet - the bayes net to use

instance - the new training instance to include in the model

Throws:

java.lang.Exception - always throws an exception, since subclass needs to be used

distributionForInstance

public double[] distributionForInstance(BayesNet bayesNet,
                                        Instance instance)
                                 throws java.lang.Exception

Calculates the class membership probabilities for the given test instance.

Parameters:

bayesNet - the bayes net to use

instance - the instance to be classified

Returns:

predicted class probability distribution

Throws:

java.lang.Exception - always throws an exception, since subclass needs to be used

initCPTs

public void initCPTs(BayesNet bayesNet)
              throws java.lang.Exception

initCPTs reserves space for CPTs and set all counts to zero

Parameters:

bayesNet - the bayes net to use

Throws:

java.lang.Exception - always throws an exception, since subclass needs to be used

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface OptionHandler

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:

 -A <alpha>
  Initial count (alpha)
 

Specified by:

setOptions in interface OptionHandler

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

Returns:

an array of strings suitable for passing to setOptions

setAlpha

public void setAlpha(double fAlpha)

Set prior used in probability table estimation

Parameters:

fAlpha - representing prior

getAlpha

public double getAlpha()

Get prior used in probability table estimation

Returns:

prior

alphaTipText

public java.lang.String alphaTipText()

Returns:

a string to describe the Alpha option.

globalInfo

public java.lang.String globalInfo()

This will return a string describing the class.

Returns:

The string.

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Returns:

the revision