weka.estimators

Class KDConditionalEstimator

java.lang.Object

weka.estimators.KDConditionalEstimator

All Implemented Interfaces:

RevisionHandler, ConditionalEstimator

public class KDConditionalEstimator
extends java.lang.Object
implements ConditionalEstimator

Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).

Version:

$Revision: 15521 $

Author:

Len Trigg (trigg@cs.waikato.ac.nz)

Constructor Summary

Constructors

Constructor and Description
KDConditionalEstimator() No-arg constructor needed to make WEKA's forName() work.
KDConditionalEstimator(int numCondSymbols, double precision) Constructor

Method Summary

Modifier and Type	Method and Description
void	addValue(double data, double given, double weight) Add a new data value to the current estimator.
Estimator	getEstimator(double given) Get a probability estimator for a value
double	getProbability(double data, double given) Get a probability estimate for a value
java.lang.String	getRevision() Returns the revision string.
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

KDConditionalEstimator

public KDConditionalEstimator()

No-arg constructor needed to make WEKA's forName() work. Uses one symbol and precision of 0.01.

KDConditionalEstimator

public KDConditionalEstimator(int numCondSymbols,
                              double precision)

Constructor

Parameters:

numCondSymbols - the number of conditioning symbols

precision - the precision to which numeric values are given. For example, if the precision is stated to be 0.1, the values in the interval (0.25,0.35] are all treated as 0.3.

Method Detail

addValue

public void addValue(double data,
                     double given,
                     double weight)

Add a new data value to the current estimator.

Specified by:

addValue in interface ConditionalEstimator

Parameters:

data - the new data value

given - the new value that data is conditional upon

weight - the weight assigned to the data value

getEstimator

public Estimator getEstimator(double given)

Get a probability estimator for a value

Specified by:

getEstimator in interface ConditionalEstimator

Parameters:

given - the new value that data is conditional upon

Returns:

the estimator for the supplied value given the condition

getProbability

public double getProbability(double data,
                             double given)

Get a probability estimate for a value

Specified by:

getProbability in interface ConditionalEstimator

Parameters:

data - the value to estimate the probability of

given - the new value that data is conditional upon

Returns:

the estimated probability of the supplied value

toString

public java.lang.String toString()

Display a representation of this estimator

Overrides:

toString in class java.lang.Object

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 pairs of integers which will be treated as numeric, symbolic.