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

    Methods
    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`

- - ### 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