Catalano.MachineLearning.Classification

Class RadiusNearestNeighbors

java.lang.Object

Catalano.MachineLearning.Classification.RadiusNearestNeighbors

All Implemented Interfaces:

IClassifier, java.io.Serializable, java.lang.Cloneable

public class RadiusNearestNeighbors
extends java.lang.Object
implements IClassifier, java.io.Serializable

Radius Neighbour classifier.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
RadiusNearestNeighbors() Initializes a new instance of the RadiusNearestNeighbors class.
RadiusNearestNeighbors(double radius) Initializes a new instance of the RadiusNearestNeighbors class.
RadiusNearestNeighbors(double radius, IDivergence divergence) Initializes a new instance of the RadiusNearestNeighbors class.
RadiusNearestNeighbors(double radius, IMercerKernel kernel) Initializes a new instance of the RadiusNearestNeighbors class.

Method Summary

Modifier and Type	Method and Description
IClassifier	clone() Clone of the object.
IDivergence	getDistance() Get the divergence function.
IMercerKernel	getKernel() Get the kernel metric.
double	getRadius() Get Radius.
void	Learn(DatasetClassification dataset) Learn from a dataset.
void	Learn(double[][] input, int[] output) Learn.
int	Predict(double[] feature) Compute.
void	setDistance(IDivergence divergence) Set the divergence function.
void	setMercerKernel(IMercerKernel kernel) Set the kernel metric.
void	setRadius(double radius) Set Radius.

Methods inherited from class java.lang.Object

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

Constructor Detail

RadiusNearestNeighbors

public RadiusNearestNeighbors()

Initializes a new instance of the RadiusNearestNeighbors class.

RadiusNearestNeighbors

public RadiusNearestNeighbors(double radius)

Initializes a new instance of the RadiusNearestNeighbors class.

Parameters:

radius - Radius.

RadiusNearestNeighbors

public RadiusNearestNeighbors(double radius,
                              IDivergence divergence)

Initializes a new instance of the RadiusNearestNeighbors class.

Parameters:

radius - Radius.

divergence - Distance.

RadiusNearestNeighbors

public RadiusNearestNeighbors(double radius,
                              IMercerKernel kernel)

Initializes a new instance of the RadiusNearestNeighbors class.

Parameters:

radius - Radius.

kernel - Kernel.

Method Detail

getRadius

public double getRadius()

Get Radius.

Returns:

Radius.

setRadius

public void setRadius(double radius)

Set Radius.

Parameters:

radius - Radius.

getKernel

public IMercerKernel getKernel()

Get the kernel metric.

Returns:

Kernel.

setMercerKernel

public void setMercerKernel(IMercerKernel kernel)

Set the kernel metric.

Parameters:

kernel - Kernel.

getDistance

public IDivergence getDistance()

Get the divergence function.

Returns:

Divergence.

setDistance

public void setDistance(IDivergence divergence)

Set the divergence function.

Parameters:

divergence - Divergence.

Learn

public void Learn(DatasetClassification dataset)

Description copied from interface: IClassifier

Learn from a dataset.

Specified by:

Learn in interface IClassifier

Parameters:

dataset - Dataset.

Learn

public void Learn(double[][] input,
                  int[] output)

Description copied from interface: IClassifier

Learn.

Specified by:

Learn in interface IClassifier

Parameters:

input - Matrix of features.

output - Labels.

Predict

public int Predict(double[] feature)

Compute.

Specified by:

Predict in interface IClassifier

Parameters:

feature - Feature to compute.

Returns:

Object.

clone

public IClassifier clone()

Description copied from interface: IClassifier

Clone of the object.

Specified by:

clone in interface IClassifier

Overrides:

clone in class java.lang.Object

Returns:

A new copy of the object.