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

private double[]	m_Counts Hold the counts
private double	m_fPrior Holds the prior probability
private int	m_nSymbols Holds number of symbols in distribution
private double	m_SumOfCounts Hold the sum of counts

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

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_Counts

private double[] m_Counts

Hold the counts

m_SumOfCounts

private double m_SumOfCounts

Hold the sum of counts

m_nSymbols

private int m_nSymbols

Holds number of symbols in distribution

m_fPrior

private double m_fPrior

Holds the prior probability

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

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.