jsat.distributions.kernels

Class RationalQuadraticKernel

java.lang.Object

jsat.distributions.kernels.BaseL2Kernel

jsat.distributions.kernels.RationalQuadraticKernel

All Implemented Interfaces:

Serializable, Cloneable, KernelTrick, Parameterized

public class RationalQuadraticKernel
extends BaseL2Kernel

Provides an implementation of the Rational Quadratic Kernel, which is of the form:
k(x, y) = 1 - ||x-y||² / (||x-y||² + c)

Author:

Edward Raff

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
RationalQuadraticKernel(double c) Creates a new RQ Kernel

Method Summary

Modifier and Type	Method and Description
RationalQuadraticKernel	clone()
double	eval(int a, int b, List<? extends Vec> trainingSet, List<Double> cache) Produces the correct kernel evaluation given the training set and the cache generated by KernelTrick.getAccelerationCache(List).
double	eval(int a, Vec b, List<Double> qi, List<? extends Vec> vecs, List<Double> cache) Computes the kernel product between one vector in the original list of vectors with that of another vector not from the original list, but had information generated by KernelTrick.getQueryInfo(jsat.linear.Vec).
double	eval(Vec a, Vec b) Evaluate this kernel function for the two given vectors.
double	getC() Returns the positive additive coefficient
static Distribution	guessC(DataSet d) Guess the distribution to use for the C parameter.
boolean	normalized() This method indicates if a kernel is a normalized kernel or not.
void	setC(double c) Sets the positive additive coefficient

Methods inherited from class jsat.distributions.kernels.BaseL2Kernel

addToCache, evalSum, evalSum, getAccelerationCache, getParameter, getParameters, getQueryInfo, getSqrdNorm, getSqrdNorm, getSqrdNorm, supportsAcceleration

Methods inherited from class java.lang.Object

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

Methods inherited from interface jsat.distributions.kernels.KernelTrick

toString

Constructor Detail

RationalQuadraticKernel

public RationalQuadraticKernel(double c)

Creates a new RQ Kernel

Parameters:

c - the positive additive coefficient

Method Detail

setC

public void setC(double c)

Sets the positive additive coefficient

Parameters:

c - the positive additive coefficient

getC

public double getC()

Returns the positive additive coefficient

Returns:

the positive additive coefficient

eval

public double eval(Vec a,
                   Vec b)

Description copied from interface: KernelTrick

Evaluate this kernel function for the two given vectors.

Specified by:

eval in interface KernelTrick

Specified by:

eval in class BaseL2Kernel

Parameters:

a - the first vector

b - the first vector

Returns:

the evaluation

eval

public double eval(int a,
                   int b,
                   List<? extends Vec> trainingSet,
                   List<Double> cache)

Description copied from interface: KernelTrick

Produces the correct kernel evaluation given the training set and the cache generated by KernelTrick.getAccelerationCache(List). The training vectors should be in the same order.

Specified by:

eval in interface KernelTrick

Specified by:

eval in class BaseL2Kernel

Parameters:

a - the index of the first training vector

b - the index of the second training vector

trainingSet - the list of training set vectors

cache - the double list of cache values generated by this kernel for the given training set

Returns:

the same kernel evaluation result as KernelTrick.eval(jsat.linear.Vec, jsat.linear.Vec)

eval

public double eval(int a,
                   Vec b,
                   List<Double> qi,
                   List<? extends Vec> vecs,
                   List<Double> cache)

Description copied from interface: KernelTrick

Computes the kernel product between one vector in the original list of vectors with that of another vector not from the original list, but had information generated by KernelTrick.getQueryInfo(jsat.linear.Vec).
If the cache input is null, then KernelTrick.eval(jsat.linear.Vec, jsat.linear.Vec) will be called directly.

Specified by:

eval in interface KernelTrick

Specified by:

eval in class BaseL2Kernel

Parameters:

a - the index of the vector in the cache

b - the other vector

qi - the query information about b

vecs - the list of vectors used to build the cache

cache - the cache associated with the given list of vectors

Returns:

the kernel product of the two vectors

clone

public RationalQuadraticKernel clone()

Specified by:

clone in interface KernelTrick

Specified by:

clone in class BaseL2Kernel

guessC

public static Distribution guessC(DataSet d)

Guess the distribution to use for the C parameter.

Parameters:

d - the data set to get the guess for

Returns:

the guess for the C parameter

See Also:

setC(double)

normalized

public boolean normalized()

Description copied from interface: KernelTrick

This method indicates if a kernel is a normalized kernel or not. A normalized kernel is one in which k(x,x) = 1 for the same object, and no value greater than 1 can be returned.

Returns:

true if this is a normalized kernel. false otherwise.