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

Constructors
Constructor Description

DiscreteEstimatorBayes(int nSymbols, double fPrior)
Constructor

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`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.

Class DiscreteEstimatorBayes

Field Summary

Fields inherited from interface weka.classifiers.bayes.net.search.local.Scoreable

Constructor Summary

Method Summary

Methods inherited from class weka.estimators.Estimator

Methods inherited from class java.lang.Object

Constructor Detail

DiscreteEstimatorBayes

Method Detail

addValue

getProbability

getCount

getNumSymbols

logScore

toString

getRevision

main