jsat.distributions.kernels

Class LinearKernel

java.lang.Object

jsat.distributions.kernels.BaseKernelTrick

jsat.distributions.kernels.LinearKernel

All Implemented Interfaces:

Serializable, Cloneable, KernelTrick, Parameterized

public class LinearKernel
extends BaseKernelTrick

Provides a linear kernel function, which computes the normal dot product. k(x,y) = x.y + c

Author:

Edward Raff

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
LinearKernel() Creates a new Linear Kernel with an added bias term of 1
LinearKernel(double c) Creates a new Linear Kernel that computes the dot product and offsets it by a specified value

Method Summary

Modifier and Type	Method and Description
LinearKernel	clone()
double	eval(Vec a, Vec b) Evaluate this kernel function for the two given vectors.
double	getC() Returns the positive additive term
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.
void	setC(double c) The positive bias term added to the result of the dot product
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

LinearKernel

public LinearKernel(double c)

Creates a new Linear Kernel that computes the dot product and offsets it by a specified value

Parameters:

c - the positive bias term for the dot product

LinearKernel

public LinearKernel()

Creates a new Linear Kernel with an added bias term of 1

Method Detail

setC

public void setC(double c)

The positive bias term added to the result of the dot product

Parameters:

c - the added product term

getC

public double getC()

Returns the positive additive term

Returns:

the positive additive term

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

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 LinearKernel clone()

Specified by:

clone in interface KernelTrick

Specified by:

clone in class BaseKernelTrick