weka.classifiers.bayes
Class DiscreteEstimatorBayes

java.lang.Object
  |
  +--weka.classifiers.bayes.DiscreteEstimatorBayes
All Implemented Interfaces:
Estimator, Scoreable, java.io.Serializable

public class DiscreteEstimatorBayes
extends java.lang.Object
implements Estimator, Scoreable

Symbolic probability estimator based on symbol counts and a prior.

Version:
$Revision: 1.4 $
Author:
Remco Bouckaert (rrb@xm.co.nz)
See Also:
Serialized Form

Field Summary
 
Fields inherited from interface weka.classifiers.bayes.Scoreable
AIC, BAYES, 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
 double logScore(int nType)
          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 java.lang.Object
equals, 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)
Method Detail

addValue

public void addValue(double data,
                     double weight)
Add a new data value to the current estimator.

Specified by:
addValue in interface 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 interface 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)
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

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.


Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London