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## weka.classifiers.bayes.net.estimate
Class BayesNetEstimator

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

All Implemented Interfaces:
  java.io.Serializable, OptionHandler

Direct Known Subclasses:
  MultiNomialBMAEstimator, SimpleEstimator

    public class BayesNetEstimator

extends java.lang.Object
implements OptionHandler, java.io.Serializable

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

Version:
  $Revision: 1.1 $
Author:
  Remco Bouckaert (rrb@xm.co.nz)
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` | `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.

  Throws:
    `java.lang.Exception`

### updateClassifier

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

  Updates the classifier with the given instance.

  Parameters:
    `instance` - the new training instance to include in the model
  Throws:
    `java.lang.Exception` - if the instance could not be incorporated in the model.

### distributionForInstance

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

  Calculates the class membership probabilities for the given test instance.

  Parameters:
    `instance` - the instance to be classified
  Returns:
    predicted class probability distribution
  Throws:
    `java.lang.Exception` - if there is a problem generating the prediction

### initCPTs

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

  initCPTs reserves space for CPTs and set all counts to zero

  Throws:
    `java.lang.Exception`

### 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:

  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.

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