Package weka.classifiers.bayes.net.estimate

Class BayesNetEstimator

java.lang.Object
weka.classifiers.bayes.net.estimate.BayesNetEstimator
All Implemented Interfaces:
Serializable, OptionHandler, RevisionHandler
Direct Known Subclasses:
MultiNomialBMAEstimator, SimpleEstimator
public class BayesNetEstimator extends Object implements OptionHandler, 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: 10153 $
Author:
Remco Bouckaert (rrb@xm.co.nz)
See Also:

  • Constructor Details

    • BayesNetEstimator

      public BayesNetEstimator()

  • Method Details

    • estimateCPTs

      public void estimateCPTs(BayesNet bayesNet) throws Exception
      estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
      Parameters:
      bayesNet - the bayes net to use
      Throws:
      Exception - always throws an exception, since subclass needs to be used

    • updateClassifier

      public void updateClassifier(BayesNet bayesNet, Instance instance) throws 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:
      Exception - always throws an exception, since subclass needs to be used

    • distributionForInstance

      public double[] distributionForInstance(BayesNet bayesNet, Instance instance) throws 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:
      Exception - always throws an exception, since subclass needs to be used

    • initCPTs

      public void initCPTs(BayesNet bayesNet) throws Exception
      initCPTs reserves space for CPTs and set all counts to zero
      Parameters:
      bayesNet - the bayes net to use
      Throws:
      Exception - always throws an exception, since subclass needs to be used

    • listOptions

      public Enumeration<Option> 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(String[] options) throws 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:
      Exception - if an option is not supported

    • getOptions

      public 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 String alphaTipText()
      Returns:
      a string to describe the Alpha option.

    • globalInfo

      public String globalInfo()
      This will return a string describing the class.
      Returns:
      The string.

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Returns:
      the revision