jsat.regression

Class NadarayaWatson

java.lang.Object

jsat.regression.NadarayaWatson

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Parameterized, Regressor

public class NadarayaWatson
extends java.lang.Object
implements Regressor, Parameterized

The Nadaraya-Watson regressor uses the Kernel Density Estimator to perform regression on a data set.
Nadaraya-Watson can also be expressed as a classifier, and equivalent results can be obtained by combining a KDE with BestClassDistribution.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
NadarayaWatson(MultivariateKDE kde)

Method Summary

Modifier and Type	Method and Description
NadarayaWatson	clone()
double	regress(DataPoint data)
boolean	supportsWeightedData()
void	train(RegressionDataSet dataSet, boolean parallel)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface jsat.regression.Regressor

train

Methods inherited from interface jsat.parameters.Parameterized

getParameter, getParameters

Constructor Detail

NadarayaWatson

public NadarayaWatson(MultivariateKDE kde)

Method Detail

regress

public double regress(DataPoint data)

Specified by:

regress in interface Regressor

train

public void train(RegressionDataSet dataSet,
                  boolean parallel)

Specified by:

train in interface Regressor

supportsWeightedData

public boolean supportsWeightedData()

Specified by:

supportsWeightedData in interface Regressor

clone

public NadarayaWatson clone()

Specified by:

clone in interface Regressor

Overrides:

clone in class java.lang.Object