Monomial kernel. Calculates \( \left\langle x_1, x_2 \right\rangle^m_exponent \). More...

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

Inheritance diagram for shark::MonomialKernel< InputType >:

Public Types
typedef base_type::BatchInputType	BatchInputType

typedef base_type::ConstInputReference	ConstInputReference

typedef base_type::ConstBatchInputReference	ConstBatchInputReference

Public Types inherited from shark::AbstractKernelFunction< InputType >
enum	Feature
	enumerations of kerneland metric features (flags) More...

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

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

typedef base_type::ConstInputReference	ConstInputReference
	Const references to InputType. More...

typedef base_type::ConstBatchInputReference	ConstBatchInputReference
	Const references to BatchInputType. More...

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

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

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

typedef Batch< InputType >::type	BatchInputType
	batch input type of the kernel More...

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

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

Public Member Functions
	MonomialKernel ()

	MonomialKernel (unsigned int n)

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

RealVector	parameterVector () const
	Return the parameter vector. More...

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

std::size_t	numberOfParameters () const
	Return the number of parameters. More...

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

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

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). More...

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

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. More...

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

void	read (InArchive &ar)
	From ISerializable, reads a metric from an archive. More...

void	write (OutArchive &ar) const
	From ISerializable, writes a metric to an archive. More...

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

const Features &	features () const

virtual void	updateFeatures ()

bool	hasFirstParameterDerivative () const

bool	hasFirstInputDerivative () const

bool	isNormalized () const

bool	supportsVariableInputSize () const

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

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

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

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

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

virtual	~AbstractMetric ()

virtual double	featureDistanceSqr (ConstInputReference x1, ConstInputReference x2) const=0
	Computes the squared distance in the kernel induced feature space. More...

virtual RealMatrix	featureDistanceSqr (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2) const=0

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

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

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

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

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

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

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Attributes
int	m_exponent
	the exponent of the monomials More...

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

Detailed Description

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

Monomial kernel. Calculates \( \left\langle x_1, x_2 \right\rangle^m_exponent \).

: The degree \( m_exponent \) is a non-trainable but configurable parameter. The default value is one - exactly the same as a LinearKernel.

Definition at line 49 of file MonomialKernel.h.

Member Typedef Documentation

§ BatchInputType

template<class InputType = RealVector>

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

Definition at line 65 of file MonomialKernel.h.

§ ConstBatchInputReference

template<class InputType = RealVector>

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

Definition at line 67 of file MonomialKernel.h.

§ ConstInputReference

template<class InputType = RealVector>

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

Definition at line 66 of file MonomialKernel.h.

Constructor & Destructor Documentation

§ MonomialKernel() [1/2]

template<class InputType = RealVector>

shark::MonomialKernel< InputType >::MonomialKernel ( )

inline

Definition at line 68 of file MonomialKernel.h.

References shark::AbstractKernelFunction< InputType >::HAS_FIRST_INPUT_DERIVATIVE, shark::AbstractKernelFunction< InputType >::HAS_FIRST_PARAMETER_DERIVATIVE, shark::AbstractKernelFunction< InputType >::m_features, and shark::AbstractKernelFunction< InputType >::SUPPORTS_VARIABLE_INPUT_SIZE.

§ MonomialKernel() [2/2]

template<class InputType = RealVector>

shark::MonomialKernel< InputType >::MonomialKernel ( unsigned int n )

inline

Definition at line 73 of file MonomialKernel.h.

References shark::AbstractKernelFunction< InputType >::HAS_FIRST_INPUT_DERIVATIVE, shark::AbstractKernelFunction< InputType >::HAS_FIRST_PARAMETER_DERIVATIVE, shark::AbstractKernelFunction< InputType >::m_features, and shark::AbstractKernelFunction< InputType >::SUPPORTS_VARIABLE_INPUT_SIZE.

Member Function Documentation

§ createState()

template<class InputType = RealVector>

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

inlinevirtual

creates the internal state of the kernel

Reimplemented from shark::AbstractKernelFunction< InputType >.

Definition at line 94 of file MonomialKernel.h.

§ eval() [1/3]

template<class InputType = RealVector>

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

inlinevirtual

Evaluates the kernel function.

Reimplemented from shark::AbstractKernelFunction< InputType >.

Definition at line 99 of file MonomialKernel.h.

References shark::blas::inner_prod(), shark::MonomialKernel< InputType >::m_exponent, shark::blas::prod(), and SIZE_CHECK.

§ eval() [2/3]

template<class InputType = RealVector>

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

inlinevirtual

Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).

The result matrix is filled in with the values result(i,j) = kernel(x1[i], x2[j]);

Reimplemented from shark::AbstractKernelFunction< InputType >.

Definition at line 105 of file MonomialKernel.h.

References shark::MonomialKernel< InputType >::m_exponent, shark::blas::noalias(), shark::blas::prod(), SIZE_CHECK, and shark::blas::trans().

§ eval() [3/3]

template<class InputType = RealVector>

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

inlinevirtual

Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).

The result matrix is filled in with the values result(i,j) = kernel(x1[i], x2[j]); The State object is filled in with data used in subsequent derivative computations.

Implements shark::AbstractKernelFunction< InputType >.

Definition at line 115 of file MonomialKernel.h.

References shark::MonomialKernel< InputType >::m_exponent, shark::blas::noalias(), shark::blas::prod(), SIZE_CHECK, shark::State::toState(), and shark::blas::trans().

§ name()

template<class InputType = RealVector>

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

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 80 of file MonomialKernel.h.

§ numberOfParameters()

template<class InputType = RealVector>

std::size_t shark::MonomialKernel< InputType >::numberOfParameters ( ) const

inlinevirtual

Return the number of parameters.

Reimplemented from shark::IParameterizable.

Definition at line 89 of file MonomialKernel.h.

§ parameterVector()

template<class InputType = RealVector>

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

inlinevirtual

Return the parameter vector.

Reimplemented from shark::IParameterizable.

Definition at line 83 of file MonomialKernel.h.

§ read()

template<class InputType = RealVector>

void shark::MonomialKernel< InputType >::read ( InArchive & archive )

inlinevirtual

From ISerializable, reads a metric from an archive.

Reimplemented from shark::AbstractMetric< InputType >.

Definition at line 179 of file MonomialKernel.h.

References shark::MonomialKernel< InputType >::m_exponent.

§ setParameterVector()

template<class InputType = RealVector>

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

inlinevirtual

Set the parameter vector.

Reimplemented from shark::IParameterizable.

Definition at line 86 of file MonomialKernel.h.

References SIZE_CHECK.

§ weightedInputDerivative()

template<class InputType = RealVector>

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

inlinevirtual

Calculates the derivative of the inputs X1 (only x1!).

The i-th row of the resulting matrix is a weighted sum of the form: c[i,0] * k'(x1[i], x2[0]) + c[i,1] * k'(x1[i], x2[1]) + ... + c[i,n] * k'(x1[i], x2[n]).

The default implementation throws a "not implemented" exception.

Reimplemented from shark::AbstractKernelFunction< InputType >.

Definition at line 150 of file MonomialKernel.h.

References shark::MonomialKernel< InputType >::m_exponent, shark::blas::noalias(), shark::blas::prod(), shark::blas::safe_div(), SIZE_CHECK, and shark::State::toState().

§ weightedParameterDerivative()

template<class InputType = RealVector>

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

inlinevirtual

Computes the gradient of the parameters as a weighted sum over the gradient of all elements of the batch.

The default implementation throws a "not implemented" exception.

Reimplemented from shark::AbstractKernelFunction< InputType >.

Definition at line 139 of file MonomialKernel.h.

References SIZE_CHECK.

§ write()

template<class InputType = RealVector>

void shark::MonomialKernel< InputType >::write ( OutArchive & archive ) const

inlinevirtual

From ISerializable, writes a metric to an archive.

The default implementation just saves the parameters.

Reimplemented from shark::AbstractMetric< InputType >.

Definition at line 183 of file MonomialKernel.h.

References shark::MonomialKernel< InputType >::m_exponent.

Member Data Documentation

§ m_exponent

template<class InputType = RealVector>

int shark::MonomialKernel< InputType >::m_exponent

protected

the exponent of the monomials

Definition at line 189 of file MonomialKernel.h.

Referenced by shark::MonomialKernel< InputType >::eval(), shark::MonomialKernel< InputType >::read(), shark::MonomialKernel< InputType >::weightedInputDerivative(), and shark::MonomialKernel< InputType >::write().

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

include/shark/Models/Kernels/MonomialKernel.h

Public Types

Public Member Functions

Protected Attributes

Detailed Description

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

Member Typedef Documentation

§ BatchInputType

§ ConstBatchInputReference

§ ConstInputReference

Constructor & Destructor Documentation

§ MonomialKernel() [1/2]

§ MonomialKernel() [2/2]

Member Function Documentation

§ createState()

§ eval() [1/3]

§ eval() [2/3]

§ eval() [3/3]

§ name()

§ numberOfParameters()

§ parameterVector()

§ read()

§ setParameterVector()

§ weightedInputDerivative()

§ weightedParameterDerivative()

§ write()

Member Data Documentation

§ m_exponent

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