ml::Kernels::Kernel Class Reference

Abstract R^D kernel interface. More...

#include <Kernels.hpp>

Inheritance diagram for ml::Kernels::Kernel:

Public Member Functions
virtual	~Kernel ()
	Virtual destructor.
virtual double	value (const Eigen::Ref< const Eigen::VectorXd > x1, const Eigen::Ref< const Eigen::VectorXd > x2) const =0
	Value of the kernel \( K(\vec{x}_1, \vec{x}_2) \). More...
virtual unsigned int	dim () const =0
	Dimension of the feature space.

Protected Member Functions
void	validate_arguments (const Eigen::Ref< const Eigen::VectorXd > x1, const Eigen::Ref< const Eigen::VectorXd > x2) const

Detailed Description

Abstract R^D kernel interface.

A kernel is a symmetric, positive-definite function \( R^D \times R^D \rightarrow R \).

Member Function Documentation

value()

virtual double ml::Kernels::Kernel::value ( const Eigen::Ref< const Eigen::VectorXd >  x1, const Eigen::Ref< const Eigen::VectorXd >  x2  ) const

pure virtual

Value of the kernel \( K(\vec{x}_1, \vec{x}_2) \).

Parameters

[in]	x1	First feature vector.
[in]	x2	Second feature vector.

Returns

Kernel value.

Exceptions

std::invalid_argument

If x1.size() != #dim() or x2.size() != #dim().

Implemented in ml::Kernels::RBFKernel< RBF >, and ml::Kernels::RBFKernel< DifferentiableRadialBasisFunction >.

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

• ML/Kernels.hpp