Gaussian radial basis function kernel. More...

#include <shark/Models/Kernels/GaussianRbfKernel.h>

Inheritance diagram for shark::GaussianRbfKernel< InputType >:

Public Types
typedef base_type::BatchInputType	BatchInputType

typedef base_type::ConstInputReference	ConstInputReference

typedef base_type::ConstBatchInputReference	ConstBatchInputReference

Public Types inherited from shark::AbstractKernelFunction< InputTypeT >
enum	Feature { HAS_FIRST_PARAMETER_DERIVATIVE = 1 , HAS_FIRST_INPUT_DERIVATIVE = 2 , IS_NORMALIZED = 4 , SUPPORTS_VARIABLE_INPUT_SIZE = 8 }
	enumerations of kerneland metric features (flags) More...

typedef base_type::InputType	InputType
	Input type of the Kernel.

typedef base_type::BatchInputType	BatchInputType
	batch input type of the kernel

typedef base_type::ConstInputReference	ConstInputReference
	Const references to InputType.

typedef base_type::ConstBatchInputReference	ConstBatchInputReference
	Const references to BatchInputType.

typedef TypedFlags< Feature >	Features
	This statement declares the member m_features. See Core/Flags.h for details.

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Public Types inherited from shark::AbstractMetric< InputTypeT >
typedef InputTypeT	InputType
	Input type of the Kernel.

typedef Batch< InputTypeT >::type	BatchInputType
	batch input type of the kernel

typedef ConstProxyReference< InputTypeconst >::type	ConstInputReference
	Const references to InputType.

typedef ConstProxyReference< BatchInputTypeconst >::type	ConstBatchInputReference
	Const references to BatchInputType.

Public Types inherited from shark::IParameterizable< VectorType >
typedef VectorType	ParameterVectorType

Public Member Functions
	GaussianRbfKernel (double gamma=1.0, bool unconstrained=false)

std::string	name () const
	From INameable: return the class name.

RealVector	parameterVector () const
	Return the parameter vector.

void	setParameterVector (RealVector const &newParameters)
	Set the parameter vector.

size_t	numberOfParameters () const
	Return the number of parameters.

double	gamma () const
	Get the bandwidth parameter value.

double	sigma () const
	Return `‘standard deviation’' of Gaussian.

void	setGamma (double gamma)

void	setSigma (double sigma)
	Set `‘standard deviation’' of Gaussian.

void	read (InArchive &ar)
	From ISerializable.

void	write (OutArchive &ar) const
	From ISerializable.

boost::shared_ptr< State >	createState () const
	creates the internal state of the kernel

double	eval (ConstInputReference x1, ConstInputReference x2) const
	evaluates \( k(x_1,x_2)\)

void	eval (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result, State &state) const
	evaluates \( k(x_1,x_2)\) and computes the intermediate value

void	eval (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result) const

void	weightedParameterDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficients, State const &state, RealVector &gradient) const

void	weightedInputDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficientsX2, State const &state, BatchInputType &gradient) const

Public Member Functions inherited from shark::AbstractKernelFunction< InputTypeT >
	AbstractKernelFunction ()

const Features &	features () const

virtual void	updateFeatures ()

bool	hasFirstParameterDerivative () const

bool	hasFirstInputDerivative () const

bool	isNormalized () const

bool	supportsVariableInputSize () const

virtual double	eval (ConstInputReference x1, ConstInputReference x2) const
	Evaluates the kernel function.

double	operator() (ConstInputReference x1, ConstInputReference x2) const
	Convenience operator which evaluates the kernel function.

virtual void	eval (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result, State &state) const =0
	Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).

virtual void	eval (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result) const
	Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).

RealMatrix	operator() (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2) const
	Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).

virtual void	weightedParameterDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficients, State const &state, RealVector &gradient) const
	Computes the gradient of the parameters as a weighted sum over the gradient of all elements of the batch.

virtual void	weightedInputDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficientsX2, State const &state, BatchInputType &gradient) const
	Calculates the derivative of the inputs X1 (only x1!).

virtual double	featureDistanceSqr (ConstInputReference x1, ConstInputReference x2) const
	Computes the squared distance in the kernel induced feature space.

virtual RealMatrix	featureDistanceSqr (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2) const
	Computes the squared distance in the kernel induced feature space.

Public Member Functions inherited from shark::AbstractMetric< InputTypeT >
	AbstractMetric ()

virtual	~AbstractMetric ()

double	featureDistance (ConstInputReference x1, ConstInputReference x2) const
	Computes the distance in the kernel induced feature space.

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

Public Member Functions inherited from shark::IParameterizable< VectorType >
virtual	~IParameterizable ()

Public Member Functions inherited from shark::ISerializable
virtual	~ISerializable ()
	Virtual d'tor.

void	load (InArchive &archive, unsigned int version)
	Versioned loading of components, calls read(...).

void	save (OutArchive &archive, unsigned int version) const
	Versioned storing of components, calls write(...).

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Attributes
double	m_gamma
	kernel bandwidth parameter

bool	m_unconstrained
	use log storage

Protected Attributes inherited from shark::AbstractKernelFunction< InputTypeT >
Features	m_features

Detailed Description

template<class InputType = RealVector>
class shark::GaussianRbfKernel< InputType >

Gaussian radial basis function kernel.

Gaussian radial basis function kernel \( k(x_1, x_2) = \exp(-\gamma \cdot \| x_1 - x_2 \|^2) \) with single bandwidth parameter \( \gamma \). Optionally, the parameter can be encoded as \( \exp(\eta) \), which allows for unconstrained optimization.

Definition at line 51 of file GaussianRbfKernel.h.

Member Typedef Documentation

◆ BatchInputType

template<class InputType = RealVector>

typedef base_type::BatchInputType shark::GaussianRbfKernel< InputType >::BatchInputType

Definition at line 66 of file GaussianRbfKernel.h.

◆ ConstBatchInputReference

template<class InputType = RealVector>

typedef base_type::ConstBatchInputReference shark::GaussianRbfKernel< InputType >::ConstBatchInputReference

Definition at line 68 of file GaussianRbfKernel.h.

◆ ConstInputReference

template<class InputType = RealVector>

typedef base_type::ConstInputReference shark::GaussianRbfKernel< InputType >::ConstInputReference

Definition at line 67 of file GaussianRbfKernel.h.

Constructor & Destructor Documentation

◆ GaussianRbfKernel()

template<class InputType = RealVector>

shark::GaussianRbfKernel< InputType >::GaussianRbfKernel	(	double	gamma = `1.0`,
		bool	unconstrained = `false`
	)

inline

Definition at line 70 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::gamma(), shark::AbstractKernelFunction< InputType >::HAS_FIRST_INPUT_DERIVATIVE, shark::AbstractKernelFunction< InputType >::HAS_FIRST_PARAMETER_DERIVATIVE, shark::AbstractKernelFunction< InputType >::IS_NORMALIZED, shark::AbstractKernelFunction< InputTypeT >::m_features, shark::GaussianRbfKernel< InputType >::m_gamma, and shark::GaussianRbfKernel< InputType >::m_unconstrained.

Member Function Documentation

◆ createState()

template<class InputType = RealVector>

boost::shared_ptr< State > shark::GaussianRbfKernel< InputType >::createState ( ) const

inlinevirtual

creates the internal state of the kernel

Reimplemented from shark::AbstractKernelFunction< InputTypeT >.

Definition at line 142 of file GaussianRbfKernel.h.

◆ eval() [1/3]

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::eval	(	ConstBatchInputReference	batchX1,
		ConstBatchInputReference	batchX2,
		RealMatrix &	result
	)		const

inline

Definition at line 176 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, and SIZE_CHECK.

◆ eval() [2/3]

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::eval	(	ConstBatchInputReference	batchX1,
		ConstBatchInputReference	batchX2,
		RealMatrix &	result,
		State &	state
	)		const

inline

evaluates \( k(x_1,x_2)\) and computes the intermediate value

Gaussian radial basis function kernel

\[ k(x_1, x_2) = \exp(-\gamma \cdot \| x_1 - x_2 \|^2) \]

Definition at line 161 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, SIZE_CHECK, and shark::State::toState().

◆ eval() [3/3]

template<class InputType = RealVector>

double shark::GaussianRbfKernel< InputType >::eval	(	ConstInputReference	x1,
		ConstInputReference	x2
	)		const

inline

evaluates \( k(x_1,x_2)\)

Gaussian radial basis function kernel

\[ k(x_1, x_2) = \exp(-\gamma \cdot \| x_1 - x_2 \|^2) \]

Definition at line 150 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, and SIZE_CHECK.

◆ gamma()

template<class InputType = RealVector>

double shark::GaussianRbfKernel< InputType >::gamma ( ) const

inline

Get the bandwidth parameter value.

Definition at line 108 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma.

Referenced by shark::GaussianRbfKernel< InputType >::GaussianRbfKernel(), main(), main(), and shark::GaussianRbfKernel< InputType >::setGamma().

◆ name()

template<class InputType = RealVector>

std::string shark::GaussianRbfKernel< InputType >::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 79 of file GaussianRbfKernel.h.

◆ numberOfParameters()

template<class InputType = RealVector>

size_t shark::GaussianRbfKernel< InputType >::numberOfParameters ( ) const

inlinevirtual

Return the number of parameters.

Reimplemented from shark::IParameterizable< VectorType >.

Definition at line 103 of file GaussianRbfKernel.h.

◆ parameterVector()

template<class InputType = RealVector>

RealVector shark::GaussianRbfKernel< InputType >::parameterVector ( ) const

inlinevirtual

Return the parameter vector.

Reimplemented from shark::IParameterizable< VectorType >.

Definition at line 82 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, and shark::GaussianRbfKernel< InputType >::m_unconstrained.

◆ read()

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::read ( InArchive & ar )

inlinevirtual

From ISerializable.

Reimplemented from shark::AbstractMetric< InputTypeT >.

Definition at line 130 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, and shark::GaussianRbfKernel< InputType >::m_unconstrained.

◆ setGamma()

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::setGamma ( double gamma )

inline

Set the bandwidth parameter value.

Exceptions

shark::Exception if gamma <= 0.

Definition at line 119 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::gamma(), shark::GaussianRbfKernel< InputType >::m_gamma, and SHARK_RUNTIME_CHECK.

◆ setParameterVector()

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::setParameterVector ( RealVector const & newParameters )

inlinevirtual

Set the parameter vector.

Reimplemented from shark::IParameterizable< VectorType >.

Definition at line 92 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, shark::GaussianRbfKernel< InputType >::m_unconstrained, and SHARK_RUNTIME_CHECK.

◆ setSigma()

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::setSigma ( double sigma )

inline

Set `‘standard deviation’' of Gaussian.

Definition at line 125 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, and shark::GaussianRbfKernel< InputType >::sigma().

◆ sigma()

template<class InputType = RealVector>

double shark::GaussianRbfKernel< InputType >::sigma ( ) const

inline

Return `‘standard deviation’' of Gaussian.

Definition at line 113 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma.

Referenced by shark::GaussianRbfKernel< InputType >::setSigma().

◆ weightedInputDerivative()

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::weightedInputDerivative	(	ConstBatchInputReference	batchX1,
		ConstBatchInputReference	batchX2,
		RealMatrix const &	coefficientsX2,
		State const &	state,
		BatchInputType &	gradient
	)		const

inline

Definition at line 206 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, SIZE_CHECK, and shark::State::toState().

◆ weightedParameterDerivative()

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::weightedParameterDerivative	(	ConstBatchInputReference	batchX1,
		ConstBatchInputReference	batchX2,
		RealMatrix const &	coefficients,
		State const &	state,
		RealVector &	gradient
	)		const

inline

Definition at line 182 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, shark::GaussianRbfKernel< InputType >::m_unconstrained, SIZE_CHECK, and shark::State::toState().

◆ write()

template<class InputType = RealVector>

void shark::GaussianRbfKernel< InputType >::write ( OutArchive & ar ) const

inlinevirtual

From ISerializable.

Reimplemented from shark::AbstractMetric< InputTypeT >.

Definition at line 136 of file GaussianRbfKernel.h.

References shark::GaussianRbfKernel< InputType >::m_gamma, and shark::GaussianRbfKernel< InputType >::m_unconstrained.

Member Data Documentation

◆ m_gamma

template<class InputType = RealVector>

double shark::GaussianRbfKernel< InputType >::m_gamma

protected

kernel bandwidth parameter

Definition at line 275 of file GaussianRbfKernel.h.

◆ m_unconstrained

template<class InputType = RealVector>

bool shark::GaussianRbfKernel< InputType >::m_unconstrained

protected

use log storage

Definition at line 276 of file GaussianRbfKernel.h.

Referenced by shark::GaussianRbfKernel< InputType >::GaussianRbfKernel(), shark::GaussianRbfKernel< InputType >::parameterVector(), shark::GaussianRbfKernel< InputType >::read(), shark::GaussianRbfKernel< InputType >::setParameterVector(), shark::GaussianRbfKernel< InputType >::weightedParameterDerivative(), and shark::GaussianRbfKernel< InputType >::write().

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

include/shark/Models/Kernels/GaussianRbfKernel.h

Public Types

Public Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ BatchInputType

◆ ConstBatchInputReference

◆ ConstInputReference

Constructor & Destructor Documentation

◆ GaussianRbfKernel()

Member Function Documentation

◆ createState()

◆ eval() [1/3]

◆ eval() [2/3]

◆ eval() [3/3]

◆ gamma()

◆ name()

◆ numberOfParameters()

◆ parameterVector()

◆ read()

◆ setGamma()

◆ setParameterVector()

◆ setSigma()

◆ sigma()

◆ weightedInputDerivative()

◆ weightedParameterDerivative()

◆ write()

Member Data Documentation

◆ m_gamma

◆ m_unconstrained