Interface Class for Kernels. More...

#include <yat/classifier/Kernel.h>

Inheritance diagram for theplu::yat::classifier::Kernel:

Public Member Functions
	Kernel (const MatrixLookup &data, const KernelFunction &kf, const bool own=false)

	Kernel (const MatrixLookupWeighted &data, const KernelFunction &kf, const bool own=false)

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

virtual	~Kernel (void)
	Destructor. More...

virtual double	operator() (const size_t row, const size_t column) const =0

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

virtual const Kernel *	make_kernel (const MatrixLookup &, const bool) const =0

virtual const Kernel *	make_kernel (const MatrixLookupWeighted &, const bool own=false) const =0

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

Interface Class for Kernels.

Class taking care of the $ NxN $ kernel matrix, where $ N $ is number of samples. Each element in the Kernel corresponds to the scalar product of the corresponding pair of samples. At the time being there are two kinds of kernels. Kernel_SEV that is optimized to be fast and Kernel_MEV that is preferable when dealing with many samples and memory might be a bottleneck. A KernelFunction defines what kind of scalar product the Kernel represents, e.g. a Polynomial Kernel of degree 1 means we are dealing with the ordinary linear scalar product.

Note: If the KernelFunction is destroyed, the Kernel is no longer defined.

Constructor & Destructor Documentation

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

Constructor taking the data matrix and KernelFunction as input. Each column in the data matrix corresponds to one sample and the Kernel matrix is built applying the KernelFunction on each pair of columns in the data matrix. If own is set to true, Kernel is owner of underlying data.

Note: Can not handle NaNs. To deal with missing values use constructor taking MatrixLookupWeighted.

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

Constructor taking the data matrix (with weights) and KernelFunction as input. Each column in the data matrix corresponds to one sample and the Kernel matrix is built applying the KernelFunction on each pair of columns in the data matrix. If own is set to true, Kernel is owner of underlying data.

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

The new kernel is created using selected features index. Kernel will own its underlying data

virtual theplu::yat::classifier::Kernel::~Kernel ( void )

virtual

Destructor.

If Kernel is owner of underlying data and Kernel is the last owner, underlying data is deleted.

Member Function Documentation

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

Returns: const reference to the underlying data.

Exceptions

if	data is weighted

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

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

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

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.

virtual const Kernel* theplu::yat::classifier::Kernel::make_kernel	(	const MatrixLookup &	,
		const bool
	)		const

pure 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.

Implemented in theplu::yat::classifier::Kernel_MEV, and theplu::yat::classifier::Kernel_SEV.

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

pure 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.

Implemented in theplu::yat::classifier::Kernel_MEV, and theplu::yat::classifier::Kernel_SEV.

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

pure virtual

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

Implemented in theplu::yat::classifier::Kernel_SEV, and theplu::yat::classifier::Kernel_MEV.

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

Returns: true if kernel is calculated using weights

Member Data Documentation

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

protected

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_

protected

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.h

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation