Special kernel function for multi-task and transfer learning. More...

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

Inheritance diagram for shark::MultiTaskKernel< InputTypeT >:

Public Types
typedef AbstractKernelFunction< InputTypeT >	InputKernelType

Public Types inherited from shark::ProductKernel< MultiTaskSample< InputTypeT > >
typedef AbstractKernelFunction< MultiTaskSample< InputTypeT > >	SubKernel

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
	MultiTaskKernel (InputKernelType inputkernel, DiscreteKernel taskkernel)
	Constructor.

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

Public Member Functions inherited from shark::ProductKernel< MultiTaskSample< InputTypeT > >
	ProductKernel ()
	Default constructor.

	ProductKernel (SubKernel k1, SubKernel k2)
	Constructor for a product of two kernels.

	ProductKernel (std::vector< SubKernel * > kernels)

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

void	addKernel (SubKernel *k)
	Add one more kernel to the expansion.

RealVector	parameterVector () const
	Return the parameter vector.

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

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

double	eval (ConstInputReference x1, ConstInputReference x2) const
	evaluates the kernel function

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).

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).

void	read (InArchive &ar)
	From ISerializable.

void	write (OutArchive &ar) const
	From ISerializable.

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

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

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 ()

Additional Inherited Members
Protected Attributes inherited from shark::ProductKernel< MultiTaskSample< InputTypeT > >
std::vector< SubKernel * >	m_kernels
	vector of sub-kernels

std::size_t	m_numberOfParameters
	total number of parameters in the product (this is redundant information)

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

Detailed Description

template<class InputTypeT>
class shark::MultiTaskKernel< InputTypeT >

Special kernel function for multi-task and transfer learning.

: This class is a convenience wrapper for the product of an input kernel and a kernel on tasks. It also encapsulates the projection from multi-task learning data (see class MultiTaskSample) to inputs and task indices.

Definition at line 297 of file MultiTaskKernel.h.

Member Typedef Documentation

◆ InputKernelType

template<class InputTypeT >

typedef AbstractKernelFunction<InputTypeT> shark::MultiTaskKernel< InputTypeT >::InputKernelType

Definition at line 305 of file MultiTaskKernel.h.

Constructor & Destructor Documentation

◆ MultiTaskKernel()

template<class InputTypeT >

shark::MultiTaskKernel< InputTypeT >::MultiTaskKernel	(	InputKernelType *	inputkernel,
		DiscreteKernel *	taskkernel
	)

inline

Constructor.

Parameters

inputkernel	kernel on inputs
taskkernel	kernel on task indices

Definition at line 310 of file MultiTaskKernel.h.

Member Function Documentation

◆ name()

template<class InputTypeT >

std::string shark::MultiTaskKernel< InputTypeT >::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 318 of file MultiTaskKernel.h.

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

include/shark/Models/Kernels/MultiTaskKernel.h

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ InputKernelType

Constructor & Destructor Documentation

◆ MultiTaskKernel()

Member Function Documentation

◆ name()