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java.lang.Object | +--weka.estimators.DiscreteEstimator
Simple symbolic probability estimator based on symbol counts.
Constructor Summary | |
DiscreteEstimator(int numSymbols,
boolean laplace)
Constructor |
|
DiscreteEstimator(int nSymbols,
double fPrior)
Constructor |
Method Summary | |
void |
addValue(double data,
double weight)
Add a new data value to the current estimator. |
int |
getNumSymbols()
Gets the number of symbols this estimator operates with |
double |
getProbability(double data)
Get a probability estimate for a value |
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 DiscreteEstimator(int numSymbols, boolean laplace)
numSymbols
- the number of possible symbols (remember to include 0)laplace
- if true, counts will be initialised to 1public DiscreteEstimator(int nSymbols, double fPrior)
nSymbols
- the number of possible symbols (remember to include 0)fPrior
- value with which counts will be initialisedMethod 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 int getNumSymbols()
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.
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Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London