|
|||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object | +--weka.classifiers.bayes.DiscreteEstimatorBayes
Symbolic probability estimator based on symbol counts and a prior.
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 |
public DiscreteEstimatorBayes(int nSymbols, double fPrior)
nSymbols
- the number of possible symbols (remember to include 0)Method Detail |
public void addValue(double data, double weight)
addValue
in interface Estimator
data
- the new data valueweight
- the weight assigned to the data valuepublic double getProbability(double data)
getProbability
in interface Estimator
data
- the value to estimate the probability of
public double getCount(double data)
data
- the value to get the counts for
public int getNumSymbols()
public double logScore(int nType)
logScore
in interface Scoreable
nType
- score type
public java.lang.String toString()
toString
in class java.lang.Object
public static void main(java.lang.String[] argv)
argv
- should contain a sequence of integers which
will be treated as symbolic.
|
|||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London