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

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

All Implemented Interfaces:
  java.io.Serializable, OptionHandler, RevisionHandler

    public class MultiNomialBMAEstimator

extends BayesNetEstimator

Multinomial BMA Estimator.

Valid options are:

     -k2
      Whether to use K2 prior.

     -A <alpha>
      Initial count (alpha)

Version:
  $Revision: 1.8 $
Author:
  Remco Bouckaert (rrb@xm.co.nz)
See Also:
  Serialized Form

Constructor Summary
`MultiNomialBMAEstimator()`

Method Summary
`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[]` | `getOptions()` Gets the current settings of the classifier.
`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
`boolean` | `isUseK2Prior()`
`java.util.Enumeration` | `listOptions()` Returns an enumeration describing the available options
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`void` | `setUseK2Prior(boolean bUseK2Prior)` Sets the UseK2Prior.
`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, setAlpha`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### MultiNomialBMAEstimator

    public MultiNomialBMAEstimator()

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 number of parents doesn't fit (more than 1)

### 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` - doesn't apply

### isUseK2Prior

    public boolean isUseK2Prior()

  Returns:
    boolean

### setUseK2Prior

    public void setUseK2Prior(boolean bUseK2Prior)

  Sets the UseK2Prior.

  Parameters:
    `bUseK2Prior` - The bUseK2Prior to set

### 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

### listOptions

    public java.util.Enumeration listOptions()

  Returns an enumeration describing the available options

  Specified by:
    `listOptions` in interface `OptionHandler`
  Overrides:
    `listOptions` in class `BayesNetEstimator`
  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:

       -k2
        Whether to use K2 prior.

       -A <alpha>
        Initial count (alpha)

  Specified by:
    `setOptions` in interface `OptionHandler`
  Overrides:
    `setOptions` in class `BayesNetEstimator`
  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`
  Overrides:
    `getOptions` in class `BayesNetEstimator`
  Returns:
    an array of strings suitable for passing to setOptions

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Overrides:
    `getRevision` in class `BayesNetEstimator`
  Returns:
    the revision

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