DiscreteEstimatorBayes

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

    java.lang.Object
      weka.estimators.Estimator
          weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, Scoreable, CapabilitiesHandler, OptionHandler, RevisionHandler

Direct Known Subclasses:
  DiscreteEstimatorFullBayes

    public class DiscreteEstimatorBayes

extends Estimator
implements Scoreable

Symbolic probability estimator based on symbol counts and a prior.

Version:
  $Revision: 1.7 $
Author:
  Remco Bouckaert (rrb@xm.co.nz)
See Also:
  Serialized Form

Field Summary

Fields inherited from interface weka.classifiers.bayes.net.search.local.Scoreable
`AIC, BAYES, BDeu, ENTROPY, MDL`

Constructor Summary
`DiscreteEstimatorBayes(int nSymbols, double fPrior)` Constructor

Method Summary
`void` | `addValue(double data, double weight)` Add a new data value to the current estimator.
`double` | `getCount(double data)` Get a counts for a value
`int` | `getNumSymbols()` Gets the number of symbols this estimator operates with
`double` | `getProbability(double data)` Get a probability estimate for a value
`java.lang.String` | `getRevision()` Returns the revision string.
`double` | `logScore(int nType, int nCardinality)` Gets the log score contribution of this distribution
`static void` | `main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.String` | `toString()` Display a representation of this estimator

Methods inherited from class weka.estimators.Estimator
`addValues, addValues, addValues, addValues, buildEstimator, buildEstimator, clone, debugTipText, equals, forName, getCapabilities, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions, testCapabilities`

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

Constructor Detail

### DiscreteEstimatorBayes

    public DiscreteEstimatorBayes(int nSymbols,
                                  double fPrior)

  Constructor

  Parameters:
    `nSymbols` - the number of possible symbols (remember to include 0)
    `fPrior` -

Method Detail

### addValue

    public void addValue(double data,
                         double weight)

  Add a new data value to the current estimator.

  Overrides:
    `addValue` in class `Estimator`
  Parameters:
    `data` - the new data value
    `weight` - the weight assigned to the data value

### getProbability

    public double getProbability(double data)

  Get a probability estimate for a value

  Specified by:
    `getProbability` in class `Estimator`
  Parameters:
    `data` - the value to estimate the probability of
  Returns:
    the estimated probability of the supplied value

### getCount

    public double getCount(double data)

  Get a counts for a value

  Parameters:
    `data` - the value to get the counts for
  Returns:
    the count of the supplied value

### getNumSymbols

    public int getNumSymbols()

  Gets the number of symbols this estimator operates with

  Returns:
    the number of estimator symbols

### logScore

    public double logScore(int nType,
                           int nCardinality)

  Gets the log score contribution of this distribution

  Specified by:
    `logScore` in interface `Scoreable`
  Parameters:
    `nType` - score type
  Returns:
    the score

### toString

    public java.lang.String toString()

  Display a representation of this estimator

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a string representation of the estimator

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Returns:
    the revision

### main

    public static void main(java.lang.String[] argv)

  Main method for testing this class.

  Parameters:
    `argv` - should contain a sequence of integers which will be treated as symbolic.

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