#include <yat/classifier/Kernel_SEV.h>

Inheritance diagram for theplu::yat::classifier::Kernel_SEV:

Public Member Functions
	Kernel_SEV (const MatrixLookup &, const KernelFunction &, const bool own=false)

	Kernel_SEV (const MatrixLookupWeighted &, const KernelFunction &, const bool own=false)

	Kernel_SEV (const Kernel_SEV &kernel, const std::vector< size_t > &index)

const Kernel_SEV *	make_kernel (const MatrixLookup &, const bool own=false) const

const Kernel_SEV *	make_kernel (const MatrixLookupWeighted &, const bool own=false) const

double	operator() (const size_t row, const size_t column) const

const MatrixLookup &	data (void) const

const MatrixLookupWeighted &	data_weighted (void) const

double	element (const DataLookup1D &vec, const size_t i) const

double	element (const DataLookupWeighted1D &vec, const size_t i) const

size_t	size (void) const
	number of samples

bool	weighted (void) const

Protected Attributes
const MatrixLookup *	ml_
	underlying data

const MatrixLookupWeighted *	mlw_
	same as data_ if weifghted otherwise a NULL pointer

const KernelFunction *	kf_
	type of Kernel Function e.g. Gaussian (aka RBF)

unsigned int *	ref_count_

unsigned int *	ref_count_w_

Detailed Description

Speed Efficient Kernel.

Class taking care of the $ NxN $ kernel matrix, where $ N $ is number of samples. Type of Kernel is defined by a KernelFunction. This Speed Efficient Version (SEV) calculates the kernel matrix once by construction and the kernel is stored in memory. When $ N $ is large and the kernel matrix cannot be stored in memory, use Kernel_MEV instead.

Constructor & Destructor Documentation

theplu::yat::classifier::Kernel_SEV::Kernel_SEV	(	const MatrixLookup &	,
		const KernelFunction &	,
		const bool	own = `false`
	)

Constructor taking the data matrix and KernelFunction as input.

Note: Can not handle NaNs. When dealing with missing values, use KernelWeighted_SEV instead.

theplu::yat::classifier::Kernel_SEV::Kernel_SEV	(	const MatrixLookupWeighted &	,
		const KernelFunction &	,
		const bool	own = `false`
	)

Constructor taking the data matrix and KernelFunction as input.

Note: Can not handle NaNs. When dealing with missing values, use KernelWeighted_SEV instead.

theplu::yat::classifier::Kernel_SEV::Kernel_SEV	(	const Kernel_SEV &	kernel,
		const std::vector< size_t > &	index
	)

Constructs a Kernel based on selected features defined by index

Member Function Documentation

const MatrixLookup& theplu::yat::classifier::Kernel::data ( void ) const

inherited

Returns: const reference to the underlying data.

Exceptions

if	data is weighted

const MatrixLookupWeighted& theplu::yat::classifier::Kernel::data_weighted ( void ) const

inherited

Returns: const reference to the underlying data.

Exceptions

if	data is unweighted

double theplu::yat::classifier::Kernel::element	(	const DataLookup1D &	vec,
		const size_t	i
	)		const

inherited

Calculates the scalar product (using the KernelFunction) between vector vec and the $ i $ th column in the data matrix.

double theplu::yat::classifier::Kernel::element	(	const DataLookupWeighted1D &	vec,
		const size_t	i
	)		const

inherited

Calculates the weighted scalar product (using the KernelFunction) between vector vec and the $ i $ th column in the data matrix. Using a weight vector with all elements equal to unity yields same result as the non-weighted version above.

const Kernel_SEV* theplu::yat::classifier::Kernel_SEV::make_kernel	(	const MatrixLookup &	,
		const bool	own = `false`
	)		const

virtual

An interface for making new classifier objects. This function allows for specification at run-time of which kernel to instatiate (see 'Prototype' in Design Patterns).

Note: Returns a dynamically allocated Kernel, which has to be deleted by the caller to avoid memory leaks.

Implements theplu::yat::classifier::Kernel.

const Kernel_SEV* theplu::yat::classifier::Kernel_SEV::make_kernel	(	const MatrixLookupWeighted &	,
		const bool	own = `false`
	)		const

virtual

An interface for making new classifier objects. This function allows for specification at run-time of which kernel to instatiate (see 'Prototype' in Design Patterns).

Note: Returns a dynamically allocated Kernel, which has to be deleted by the caller to avoid memory leaks.

Implements theplu::yat::classifier::Kernel.

double theplu::yat::classifier::Kernel_SEV::operator()	(	const size_t	row,
		const size_t	column
	)		const

virtual

Returns: element at position (row, column) in the Kernel matrix

Implements theplu::yat::classifier::Kernel.

bool theplu::yat::classifier::Kernel::weighted ( void ) const

inherited

Returns: true if kernel is calculated using weights

Member Data Documentation

unsigned int* theplu::yat::classifier::Kernel::ref_count_

protectedinherited

pointer telling how many owners to underlying data (data_). NULL if this is not an owner.

unsigned int* theplu::yat::classifier::Kernel::ref_count_w_

protectedinherited

pointer telling how many owners to underlying weights (data_w_). NULL if this is not an owner.

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

yat/classifier/Kernel_SEV.h

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation