weka.estimators

Class KernelEstimator

java.lang.Object

weka.estimators.Estimator

weka.estimators.KernelEstimator

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Aggregateable<KernelEstimator>, CapabilitiesHandler, CapabilitiesIgnorer, OptionHandler, RevisionHandler, IncrementalEstimator

public class KernelEstimator
extends Estimator
implements IncrementalEstimator, Aggregateable<KernelEstimator>

Simple kernel density estimator. Uses one gaussian kernel per observed data value.

Version:

$Revision: 15522 $

Author:

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
KernelEstimator() No-arg constructor needed to make WEKA's forName() work.
KernelEstimator(double precision) Constructor that takes a precision argument.

Method Summary

Modifier and Type	Method and Description
void	addValue(double data, double weight) Add a new data value to the current estimator.
KernelEstimator	aggregate(KernelEstimator toAggregate) Aggregate an object with this one
void	finalizeAggregation() Call to complete the aggregation process.
Capabilities	getCapabilities() Returns default capabilities of the classifier.
double[]	getMeans() Return the means of the kernels.
int	getNumKernels() Return the number of kernels in this kernel estimator
double	getPrecision() Return the precision of this kernel estimator.
double	getProbability(double data) Get a probability estimate for a value.
java.lang.String	getRevision() Returns the revision string.
double	getStdDev() Return the standard deviation of this kernel estimator.
double[]	getWeights() Return the weights of the kernels.
static void	main(java.lang.String[] argv) Main method for testing this class.
static void	testAggregation()
java.lang.String	toString() Display a representation of this estimator

Methods inherited from class weka.estimators.Estimator

addValues, addValues, addValues, addValues, buildEstimator, buildEstimator, clone, debugTipText, doNotCheckCapabilitiesTipText, equals, forName, getDebug, getDoNotCheckCapabilities, getOptions, listOptions, makeCopies, makeCopy, setDebug, setDoNotCheckCapabilities, setOptions, testCapabilities

Methods inherited from class java.lang.Object

getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

KernelEstimator

public KernelEstimator()

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

KernelEstimator

public KernelEstimator(double precision)

Constructor that takes a precision argument.

Parameters:

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 weight)

Add a new data value to the current estimator.

Specified by:

addValue in interface IncrementalEstimator

Overrides:

addValue in class 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 class Estimator

Parameters:

data - the value to estimate the probability of

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

getNumKernels

public int getNumKernels()

Return the number of kernels in this kernel estimator

Returns:

the number of kernels

getMeans

public double[] getMeans()

Return the means of the kernels.

Returns:

the means of the kernels

getWeights

public double[] getWeights()

Return the weights of the kernels.

Returns:

the weights of the kernels

getPrecision

public double getPrecision()

Return the precision of this kernel estimator.

Returns:

the precision

getStdDev

public double getStdDev()

Return the standard deviation of this kernel estimator.

Returns:

the standard deviation

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class Estimator

Returns:

the capabilities of this classifier

See Also:

Capabilities

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class Estimator

Returns:

the revision

aggregate

public KernelEstimator aggregate(KernelEstimator toAggregate)
                          throws java.lang.Exception

Description copied from interface: Aggregateable

Aggregate an object with this one

Specified by:

aggregate in interface Aggregateable<KernelEstimator>

Parameters:

toAggregate - the object to aggregate

Returns:

the result of aggregation

Throws:

java.lang.Exception - if the supplied object can't be aggregated for some reason

finalizeAggregation

public void finalizeAggregation()
                         throws java.lang.Exception

Description copied from interface: Aggregateable

Call to complete the aggregation process. Allows implementers to do any final processing based on how many objects were aggregated.

Specified by:

finalizeAggregation in interface Aggregateable<KernelEstimator>

Throws:

java.lang.Exception - if the aggregation can't be finalized for some reason

testAggregation

public static void testAggregation()

main

public static void main(java.lang.String[] argv)

Main method for testing this class.

Parameters:

argv - should contain a sequence of numeric values