ml::Kernels::GaussianRBF Class Reference

Gaussian radial basis function. More...

#include <Kernels.hpp>

Inheritance diagram for ml::Kernels::GaussianRBF:

Collaboration diagram for ml::Kernels::GaussianRBF:

Public Member Functions
double	value (double r2) const override
	Radial basis function of the RBF kernel. More...
double	gradient (double r2) const override
	Gradient of the radial basis function of the RBF kernel. More...
double	second_derivative (double r2) const override
	Second derivative of the radial basis function of the RBF kernel. More...
Public Member Functions inherited from ml::Kernels::RadialBasisFunction
virtual	~RadialBasisFunction ()
	Virtual destructor.

Detailed Description

Gaussian radial basis function.

Given by the formula f(r2) = exp(-r2), where r2 is the SQUARE of the norm.

Member Function Documentation

value()

double ml::Kernels::GaussianRBF::value ( double  r2 ) const

overridevirtual

Radial basis function of the RBF kernel.

Parameters

r2	Square of the L2 norm of the difference between two feature vectors.

Returns

Kernel value.

Exceptions

std::domain_error

If r2 < 0.

Implements ml::Kernels::RadialBasisFunction.

gradient()

double ml::Kernels::GaussianRBF::gradient ( double  r2 ) const

overridevirtual

Gradient of the radial basis function of the RBF kernel.

Parameters

r2	Square of the L2 norm of the difference between two feature vectors.

Returns

Kernel value.

Exceptions

std::domain_error

If r2 < 0.

Implements ml::Kernels::DifferentiableRadialBasisFunction.

second_derivative()

double ml::Kernels::GaussianRBF::second_derivative ( double  r2 ) const

overridevirtual

Second derivative of the radial basis function of the RBF kernel.

Parameters

r2	Square of the L2 norm of the difference between two feature vectors.

Returns

Kernel value.

Exceptions

std::domain_error

If r2 < 0.

Implements ml::Kernels::DoubleDifferentiableRadialBasisFunction.

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The documentation for this class was generated from the following file:

• ML/Kernels.hpp