weka.classifiers.bayes.net.estimate

Class SimpleEstimator

java.lang.Object

weka.classifiers.bayes.net.estimate.BayesNetEstimator

weka.classifiers.bayes.net.estimate.SimpleEstimator

All Implemented Interfaces:

java.io.Serializable, OptionHandler, RevisionHandler

Direct Known Subclasses:

BMAEstimator

public class SimpleEstimator
extends BayesNetEstimator

SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has been learned. Estimates probabilities directly from data.

Valid options are:

 -A <alpha>
  Initial count (alpha)
 

Version:

$Revision: 11325 $

Author:

Remco Bouckaert (rrb@xm.co.nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
SimpleEstimator()

Method Summary

Modifier and Type	Method and Description
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.
java.lang.String	getRevision() Returns the revision string.
java.lang.String	globalInfo() Returns a string describing this object
void	initCPTs(BayesNet bayesNet) initCPTs reserves space for CPTs and set all counts to zero
void	updateClassifier(BayesNet bayesNet, Instance instance) Updates the classifier with the given instance.

Methods inherited from class weka.classifiers.bayes.net.estimate.BayesNetEstimator

alphaTipText, getAlpha, getOptions, listOptions, setAlpha, setOptions

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

SimpleEstimator

public SimpleEstimator()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this object

Overrides:

globalInfo in class BayesNetEstimator

Returns:

a description of the classifier suitable for displaying in the explorer/experimenter gui

estimateCPTs

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

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

Overrides:

estimateCPTs in class BayesNetEstimator

Parameters:

bayesNet - the bayes net to use

Throws:

java.lang.Exception - if something goes wrong

updateClassifier

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

Updates the classifier with the given instance.

Overrides:

updateClassifier in class BayesNetEstimator

Parameters:

bayesNet - the bayes net to use

instance - the new training instance to include in the model

Throws:

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

initCPTs

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

initCPTs reserves space for CPTs and set all counts to zero

Overrides:

initCPTs in class BayesNetEstimator

Parameters:

bayesNet - the bayes net to use

Throws:

java.lang.Exception - if something goes wrong

distributionForInstance

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

Calculates the class membership probabilities for the given test instance.

Overrides:

distributionForInstance in class BayesNetEstimator

Parameters:

bayesNet - the bayes net to use

instance - the instance to be classified

Returns:

predicted class probability distribution

Throws:

java.lang.Exception - if there is a problem generating the prediction

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class BayesNetEstimator

Returns:

the revision