Catalano.MachineLearning.Classification

Class MulticlassSupportVectorMachine

java.lang.Object

Catalano.MachineLearning.Classification.MulticlassSupportVectorMachine

All Implemented Interfaces:

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

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

Multiclass Support Vector Machine.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MulticlassSupportVectorMachine(IMercerKernel kernel, double c, double[] weight) Initializes a new instance of the MulticlassSupportVectorMachine class.
MulticlassSupportVectorMachine(IMercerKernel kernel, double c, double[] weight, SVM.Strategy strategy) Initializes a new instance of the MulticlassSupportVectorMachine class.
MulticlassSupportVectorMachine(IMercerKernel kernel, double c, int numberOfClasses) Initializes a new instance of the MulticlassSupportVectorMachine class.
MulticlassSupportVectorMachine(IMercerKernel kernel, double c, int numberOfClasses, SVM.Strategy strategy) Initializes a new instance of the MulticlassSupportVectorMachine class.

Method Summary

Modifier and Type	Method and Description
IClassifier	clone() Clone of the object.
void	Finish() Process support vectors until convergence.
void	Learn(DatasetClassification dataset) Learn from a dataset.
void	Learn(double[][] input, int[] output) Learn.
void	Learn(double[] input, int output) Online learn.
int	Predict(double[] feature) Predict.

Methods inherited from class java.lang.Object

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

Constructor Detail

MulticlassSupportVectorMachine

public MulticlassSupportVectorMachine(IMercerKernel kernel,
                                      double c,
                                      int numberOfClasses)

Initializes a new instance of the MulticlassSupportVectorMachine class.

Parameters:

kernel - Mercer kernel.

c - Soft margin penalty parameter.

numberOfClasses - Number of classes.

MulticlassSupportVectorMachine

public MulticlassSupportVectorMachine(IMercerKernel kernel,
                                      double c,
                                      int numberOfClasses,
                                      SVM.Strategy strategy)

Initializes a new instance of the MulticlassSupportVectorMachine class.

Parameters:

kernel - Mercer kernel.

c - Soft margin penalty parameter.

numberOfClasses - Number of classes.

strategy - Strategy.

MulticlassSupportVectorMachine

public MulticlassSupportVectorMachine(IMercerKernel kernel,
                                      double c,
                                      double[] weight)

Initializes a new instance of the MulticlassSupportVectorMachine class.

Parameters:

kernel - Mercer kernel.

c - Soft margin penalty parameter.

weight - Class weight.

MulticlassSupportVectorMachine

public MulticlassSupportVectorMachine(IMercerKernel kernel,
                                      double c,
                                      double[] weight,
                                      SVM.Strategy strategy)

Initializes a new instance of the MulticlassSupportVectorMachine class.

Parameters:

kernel - Mercer kernel.

c - Soft margin penalty parameter.

weight - Class weight.

strategy - Strategy.

Method Detail

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.

Learn

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

Online learn.

Parameters:

input - Feature.

output - Label.

Predict

public int Predict(double[] feature)

Description copied from interface: IClassifier

Predict.

Specified by:

Predict in interface IClassifier

Parameters:

feature - Feature.

Returns:

Label.

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.

Finish

public void Finish()

Process support vectors until convergence.