Catalano.MachineLearning.Classification

Class SparseSupportVectorMachine

java.lang.Object

Catalano.MachineLearning.Classification.SparseSupportVectorMachine

All Implemented Interfaces:

java.io.Serializable

public class SparseSupportVectorMachine
extends java.lang.Object
implements java.io.Serializable

Sparse Support Vector Machine.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
SparseSupportVectorMachine(IMercerKernel kernel, double c) Initializes a new instance of the SparseSupportVectorMachine class.
SparseSupportVectorMachine(IMercerKernel kernel, double c, double cn) Initializes a new instance of the SparseSupportVectorMachine class.

Method Summary

Modifier and Type	Method and Description
void	Finish()
void	Learn(SparseArray[] input, int[] output)
void	Learn(SparseArray input, int output) Online learn.
int	Predict(SparseArray feature)

Methods inherited from class java.lang.Object

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

Constructor Detail

SparseSupportVectorMachine

public SparseSupportVectorMachine(IMercerKernel kernel,
                                  double c)

Initializes a new instance of the SparseSupportVectorMachine class.

Parameters:

kernel - Mercer kernel.

c - Soft margin penalty parameter.

SparseSupportVectorMachine

public SparseSupportVectorMachine(IMercerKernel kernel,
                                  double c,
                                  double cn)

Initializes a new instance of the SparseSupportVectorMachine class.

Parameters:

kernel - Mercer kernel.

c - Soft margin penalty parameter for positive instances.

cn - Soft margin penalty parameter for negative instances.

Method Detail

Learn

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

Learn

public void Learn(SparseArray input,
                  int output)

Online learn.

Parameters:

input - Feature.

output - Label.

Predict

public int Predict(SparseArray feature)

Finish

public void Finish()