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Class weka.classifiers.functions.supportVector.Kernel 

java.lang.Object
    |
    +----weka.classifiers.functions.supportVector.Kernel
public abstract class Kernel
extends java.lang.Object
implements java.io.Serializable
Abstract kernel. Kernels implementing this class must respect Mercer's condition in order to ensure a correct behaviour of SMOreg.

Version:
$$
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

Constructor Index

o Kernel()
 

Method Index

o clean()
Frees the memory used by the kernel.
o eval(int, int, Instance)
Computes the result of the kernel function for two instances.
o numEvals()
Returns the number of kernel evaluation performed.

Constructor Detail

o Kernel
public Kernel()

Method Detail

o eval
public abstract double eval(int id1,
                            int id2,
                            Instance inst1) throws java.lang.Exception
          Computes the result of the kernel function for two instances. If id1 == -1, eval use inst1 instead of an instance in the dataset.
Parameters:
id1 - the index of the first instance in the dataset
id2 - the index of the second instance in the dataset
inst - the instance corresponding to id1 (used if id1 == -1)
Returns:
the result of the kernel function
o clean
public abstract void clean()
          Frees the memory used by the kernel. (Usefull with kernels which use cache.) This function is called when the training is done. i.e. after that, eval will be called with id1 == -1.
o numEvals
public abstract int numEvals()
          Returns the number of kernel evaluation performed.
Returns:
the number of kernel evaluation performed.
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