jsat.distributions.kernels

Class PolynomialKernel

java.lang.Object

jsat.distributions.kernels.BaseKernelTrick

jsat.distributions.kernels.PolynomialKernel

All Implemented Interfaces:

Serializable, Cloneable, KernelTrick, Parameterized

public class PolynomialKernel
extends BaseKernelTrick

Provides a Polynomial Kernel of the form
k(x,y) = (alpha * x.y + c)^d

Author:

Edward Raff

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
PolynomialKernel(double degree) Defaults alpha = 1 and c = 1
PolynomialKernel(double degree, double alpha, double c) Creates a new polynomial kernel

Method Summary

Modifier and Type	Method and Description
PolynomialKernel	clone()
double	eval(Vec a, Vec b) Evaluate this kernel function for the two given vectors.
double	getAlpha() Returns the scaling parameter
double	getC() Returns the additive constant
double	getDegree() Returns the degree of the polynomial
Parameter	getParameter(String paramName) Returns the parameter with the given name.
List<Parameter>	getParameters() Returns the list of parameters that can be altered for this learner.
static Distribution	guessDegree(DataSet d) Guesses the distribution to use for the degree parameter
void	setAlpha(double alpha) Sets the scaling factor for the dot product, this is equivalent to multiplying each value in the data set by a constant factor
void	setC(double c) Sets the additive term, when set to one this is equivalent to adding a bias term of 1 to each vector.
void	setDegree(double d) Sets the degree of the polynomial
String	toString() A descriptive name for the type of KernelFunction

Methods inherited from class jsat.distributions.kernels.BaseKernelTrick

addToCache, eval, eval, evalSum, evalSum, getAccelerationCache, getQueryInfo, normalized, supportsAcceleration

Methods inherited from class java.lang.Object

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

Constructor Detail

PolynomialKernel

public PolynomialKernel(double degree,
                        double alpha,
                        double c)

Creates a new polynomial kernel

Parameters:

degree - the degree of the polynomial

alpha - the term to scale the dot product by

c - the additive term

PolynomialKernel

public PolynomialKernel(double degree)

Defaults alpha = 1 and c = 1

Parameters:

degree - the degree of the polynomial

Method Detail

setAlpha

public void setAlpha(double alpha)

Sets the scaling factor for the dot product, this is equivalent to multiplying each value in the data set by a constant factor

Parameters:

alpha - the scaling factor

setC

public void setC(double c)

Sets the additive term, when set to one this is equivalent to adding a bias term of 1 to each vector. This is done after the scaling by alpha.

Parameters:

c - the non negative additive term

setDegree

public void setDegree(double d)

Sets the degree of the polynomial

Parameters:

d - the degree of the polynomial

getAlpha

public double getAlpha()

Returns the scaling parameter

Returns:

the scaling parameter

getC

public double getC()

Returns the additive constant

Returns:

the additive constant

getDegree

public double getDegree()

Returns the degree of the polynomial

Returns:

the degree of the polynomial

eval

public double eval(Vec a,
                   Vec b)

Description copied from interface: KernelTrick

Evaluate this kernel function for the two given vectors.

Parameters:

a - the first vector

b - the first vector

Returns:

the evaluation

toString

public String toString()

Description copied from interface: KernelTrick

A descriptive name for the type of KernelFunction

Specified by:

toString in interface KernelTrick

Overrides:

toString in class Object

Returns:

a descriptive name for the type of KernelFunction

guessDegree

public static Distribution guessDegree(DataSet d)

Guesses the distribution to use for the degree parameter

Parameters:

d - the dataset to get the guess for

Returns:

the guess for the degree parameter

See Also:

setDegree(double)

getParameters

public List<Parameter> getParameters()

Description copied from interface: Parameterized

Returns the list of parameters that can be altered for this learner.

Returns:

the list of parameters that can be altered for this learner.

getParameter

public Parameter getParameter(String paramName)

Description copied from interface: Parameterized

Returns the parameter with the given name. Two different strings may map to a single Parameter object. An ASCII only string, and a Unicode style string.

Parameters:

paramName - the name of the parameter to obtain

Returns:

the Parameter in question, or null if no such named Parameter exists.

clone

public PolynomialKernel clone()

Specified by:

clone in interface KernelTrick

Specified by:

clone in class BaseKernelTrick