weka.classifiers.functions.supportVector
Class PolyKernel

java.lang.Object
  weka.classifiers.functions.supportVector.Kernel
      weka.classifiers.functions.supportVector.PolyKernel

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

NormalizedPolyKernel

public class PolyKernel

extends Kernel

The polynomial kernel : K(x, y) = ^p or K(x, y) = (+1)^p

Version:

$$

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Shane Legg (shane@intelligenesis.net) (sparse vector code), Stuart Inglis (stuart@reeltwo.com) (sparse vector code)

See Also:

Serialized Form

Field Summary

private int	m_cacheSize The size of the cache (a prime number)
private double	m_exponent The exponent for the polynomial kernel.
private int	m_kernelEvals Counts the number of kernel evaluations.
private long[]	m_keys
private boolean	m_lowerOrder Use lower-order terms?
private int	m_numInsts The number of instance in the dataset
private double[]	m_storage Kernel cache

Fields inherited from class weka.classifiers.functions.supportVector.Kernel

m_data

Constructor Summary

PolyKernel(Instances dataset, int cacheSize, double exponent, boolean lowerOrder)
Creates a new PolyKernel instance.

Method Summary

void	clean() Frees the cache used by the kernel.
private double	dotProd(Instance inst1, Instance inst2) Calculates a dot product between two instances
double	eval(int id1, int id2, Instance inst1) Implements the abstract function of Kernel.
int	numEvals() Returns the number of time Eval has been called.

Methods inherited from class java.lang.Object

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

Field Detail

m_cacheSize

private int m_cacheSize

The size of the cache (a prime number)

m_lowerOrder

private boolean m_lowerOrder

Use lower-order terms?

m_exponent

private double m_exponent

The exponent for the polynomial kernel.

m_storage

private double[] m_storage

Kernel cache

m_keys

private long[] m_keys

m_kernelEvals

private int m_kernelEvals

Counts the number of kernel evaluations.

m_numInsts

private int m_numInsts

The number of instance in the dataset

Constructor Detail

PolyKernel

public PolyKernel(Instances dataset,
                  int cacheSize,
                  double exponent,
                  boolean lowerOrder)

Creates a new PolyKernel instance.

Parameters:

dataset - the training dataset used.

cacheSize - the size of the cache (a prime number)

Method Detail

eval

public double eval(int id1,
                   int id2,
                   Instance inst1)
            throws java.lang.Exception

Implements the abstract function of Kernel.

Specified by:

eval in class Kernel

Parameters:

id1 - the index of the first instance in the dataset

id2 - the index of the second instance in the dataset

Returns:

the result of the kernel function

Throws:

java.lang.Exception

dotProd

private double dotProd(Instance inst1,
                       Instance inst2)
                throws java.lang.Exception

Calculates a dot product between two instances

Parameters:

inst1 - the first instance

inst2 - the second instance

Returns:

the dot product of the two instances.

Throws:

java.lang.Exception - if an error occurs

clean

public void clean()

Frees the cache used by the kernel.

Specified by:

clean in class Kernel

numEvals

public int numEvals()

Returns the number of time Eval has been called.

Specified by:

numEvals in class Kernel

Returns:

the number of kernel evaluation.