Detailed Description

The Weighted Degree String kernel.

The WD kernel of order d compares two sequences \({\bf x}\) and \({\bf x'}\) of length L by summing all contributions of k-mer matches of lengths \(k\in\{1,\dots,d\}\), weighted by coefficients \(\beta_k\). It is defined as

\[ k({\bf x},{\bf x'})=\sum_{k=1}^d\beta_k\sum_{l=1}^{L-k+1}I({\bf u}_{k,l}({\bf x})={\bf u}_{k,l}({\bf x'})). \]

Here, \({\bf u}_{k,l}({\bf x})\) is the string of length k starting at position l of the sequence \({\bf x}\) and \(I(\cdot)\) is the indicator function which evaluates to 1 when its argument is true and to 0 otherwise.

Definition at line 55 of file WeightedDegreeStringKernel.h.

Inheritance diagram for CWeightedDegreeStringKernel:

[legend]

Public Member Functions
	CWeightedDegreeStringKernel ()

	CWeightedDegreeStringKernel (int32_t degree, EWDKernType type=E_WD)

	CWeightedDegreeStringKernel (SGVector< float64_t > weights)

	CWeightedDegreeStringKernel (CStringFeatures< char > l, CStringFeatures< char > r, int32_t degree)

virtual	~CWeightedDegreeStringKernel ()

virtual bool	init (CFeatures l, CFeatures r)

virtual void	cleanup ()

EWDKernType	get_type () const

virtual EKernelType	get_kernel_type ()

virtual const char *	get_name () const

virtual bool	init_optimization (int32_t count, int32_t IDX, float64_t alphas)

virtual bool	init_optimization (int32_t count, int32_t IDX, float64_t alphas, int32_t tree_num)

virtual bool	delete_optimization ()

virtual float64_t	compute_optimized (int32_t idx)

virtual void	compute_batch (int32_t num_vec, int32_t vec_idx, float64_t target, int32_t num_suppvec, int32_t IDX, float64_t alphas, float64_t factor=1.0)

virtual void	clear_normal ()

virtual void	add_to_normal (int32_t idx, float64_t weight)

virtual int32_t	get_num_subkernels ()

void	compute_by_subkernel (int32_t idx, float64_t *subkernel_contrib)

const float64_t *	get_subkernel_weights (int32_t &num_weights)

virtual void	set_subkernel_weights (SGVector< float64_t > w)

virtual bool	set_normalizer (CKernelNormalizer *normalizer_)

float64_t *	compute_abs_weights (int32_t &len)

void	compute_by_tree (int32_t idx, float64_t *LevelContrib)

bool	is_tree_initialized ()

float64_t *	get_degree_weights (int32_t &d, int32_t &len)

float64_t *	get_weights (int32_t &num_weights)

float64_t *	get_position_weights (int32_t &len)

bool	set_wd_weights_by_type (EWDKernType type)

void	set_wd_weights (SGVector< float64_t > new_weights)

bool	set_weights (SGMatrix< float64_t > new_weights)

bool	set_position_weights (float64_t *pws, int32_t len)

bool	init_block_weights ()

bool	init_block_weights_from_wd ()

bool	init_block_weights_from_wd_external ()

bool	init_block_weights_const ()

bool	init_block_weights_linear ()

bool	init_block_weights_sqpoly ()

bool	init_block_weights_cubicpoly ()

bool	init_block_weights_exp ()

bool	init_block_weights_log ()

bool	delete_position_weights ()

bool	set_max_mismatch (int32_t max)

int32_t	get_max_mismatch () const

bool	set_degree (int32_t deg)

int32_t	get_degree () const

bool	set_use_block_computation (bool block)

bool	get_use_block_computation ()

bool	set_mkl_stepsize (int32_t step)

int32_t	get_mkl_stepsize ()

bool	set_which_degree (int32_t which)

int32_t	get_which_degree ()

virtual EFeatureClass	get_feature_class ()

virtual EFeatureType	get_feature_type ()

float64_t	kernel (int32_t idx_a, int32_t idx_b)

SGMatrix< float64_t >	get_kernel_matrix ()

template<class T >
SGMatrix< T >	get_kernel_matrix ()

SGVector< float64_t >	get_kernel_diagonal (SGVector< float64_t > preallocated=SGVector< float64_t >())

virtual SGVector< float64_t >	get_kernel_col (int32_t j)

virtual SGVector< float64_t >	get_kernel_row (int32_t i)

void	get_kernel_row (int32_t docnum, int32_t active2dnum, float64_t buffer, bool full_line=false)

virtual float64_t	sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true)

virtual float64_t	sum_block (index_t block_begin_row, index_t block_begin_col, index_t block_size_row, index_t block_size_col, bool no_diag=false)

virtual SGVector< float64_t >	row_wise_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true)

virtual SGMatrix< float64_t >	row_wise_sum_squared_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true)

virtual SGVector< float64_t >	row_col_wise_sum_block (index_t block_begin_row, index_t block_begin_col, index_t block_size_row, index_t block_size_col, bool no_diag=false)

virtual CKernelNormalizer *	get_normalizer ()

virtual bool	init_normalizer ()

void	load (CFile *loader)

void	save (CFile *writer)

CFeatures *	get_lhs ()

CFeatures *	get_rhs ()

virtual int32_t	get_num_vec_lhs ()

virtual int32_t	get_num_vec_rhs ()

virtual bool	has_features ()

bool	get_lhs_equals_rhs ()

virtual void	remove_lhs_and_rhs ()

virtual void	remove_rhs ()
	takes all necessary steps if the rhs is removed from kernel More...

void	set_cache_size (int32_t size)

int32_t	get_cache_size ()

void	cache_reset ()

int32_t	get_max_elems_cache ()

int32_t	get_activenum_cache ()

void	cache_kernel_row (int32_t x)

void	cache_multiple_kernel_rows (int32_t *key, int32_t varnum)

void	kernel_cache_reset_lru ()

void	kernel_cache_shrink (int32_t totdoc, int32_t num_shrink, int32_t *after)

void	resize_kernel_cache (KERNELCACHE_IDX size, bool regression_hack=false)

void	set_time (int32_t t)

int32_t	kernel_cache_touch (int32_t cacheidx)

int32_t	kernel_cache_check (int32_t cacheidx)

int32_t	kernel_cache_space_available ()

void	kernel_cache_init (int32_t size, bool regression_hack=false)

void	kernel_cache_cleanup ()

void	list_kernel ()

bool	has_property (EKernelProperty p)

EOptimizationType	get_optimization_type ()

virtual void	set_optimization_type (EOptimizationType t)

bool	get_is_initialized ()

bool	init_optimization_svm (CSVM *svm)

float64_t	get_combined_kernel_weight ()

void	set_combined_kernel_weight (float64_t nw)

virtual SGVector< float64_t >	get_subkernel_weights ()

virtual SGMatrix< float64_t >	get_parameter_gradient (const TParameter *param, index_t index=-1)

virtual SGVector< float64_t >	get_parameter_gradient_diagonal (const TParameter *param, index_t index=-1)

virtual CSGObject *	shallow_copy () const

virtual CSGObject *	deep_copy () const

virtual bool	is_generic (EPrimitiveType *generic) const

template<class T >
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

template<>
void	set_generic ()

void	unset_generic ()

virtual void	print_serializable (const char *prefix="")

virtual bool	save_serializable (CSerializableFile file, const char prefix="")

virtual bool	load_serializable (CSerializableFile file, const char prefix="")

void	set_global_io (SGIO *io)

SGIO *	get_global_io ()

void	set_global_parallel (Parallel *parallel)

Parallel *	get_global_parallel ()

void	set_global_version (Version *version)

Version *	get_global_version ()

SGStringList< char >	get_modelsel_names ()

void	print_modsel_params ()

char *	get_modsel_param_descr (const char *param_name)

index_t	get_modsel_param_index (const char *param_name)

void	build_gradient_parameter_dictionary (CMap< TParameter , CSGObject > *dict)

virtual void	update_parameter_hash ()

virtual bool	parameter_hash_changed ()

virtual bool	equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)

virtual CSGObject *	clone ()

Static Public Member Functions
static void *	compute_batch_helper (void *p)

static CKernel *	obtain_from_generic (CSGObject *kernel)

Public Attributes
SGIO *	io

Parallel *	parallel

Version *	version

Parameter *	m_parameters

Parameter *	m_model_selection_parameters

Parameter *	m_gradient_parameters

uint32_t	m_hash

Protected Member Functions
void	create_empty_tries ()

void	add_example_to_tree (int32_t idx, float64_t weight)

void	add_example_to_single_tree (int32_t idx, float64_t weight, int32_t tree_num)

void	add_example_to_tree_mismatch (int32_t idx, float64_t weight)

void	add_example_to_single_tree_mismatch (int32_t idx, float64_t weight, int32_t tree_num)

float64_t	compute_by_tree (int32_t idx)

float64_t	compute (int32_t idx_a, int32_t idx_b)

float64_t	compute_with_mismatch (char avec, int32_t alen, char bvec, int32_t blen)

float64_t	compute_without_mismatch (char avec, int32_t alen, char bvec, int32_t blen)

float64_t	compute_without_mismatch_matrix (char avec, int32_t alen, char bvec, int32_t blen)

float64_t	compute_using_block (char avec, int32_t alen, char bvec, int32_t blen)

virtual void	remove_lhs ()

void	set_property (EKernelProperty p)

void	unset_property (EKernelProperty p)

void	set_is_initialized (bool p_init)

int32_t	compute_row_start (int64_t offs, int32_t n, bool symmetric)

virtual void	load_serializable_post () throw (ShogunException)

virtual void	save_serializable_pre () throw (ShogunException)

virtual void	save_serializable_post () throw (ShogunException)

virtual void	register_params ()

virtual void	load_serializable_pre () throw (ShogunException)

Static Protected Member Functions
template<class T >
static void *	get_kernel_matrix_helper (void *p)

Protected Attributes
float64_t *	weights

int32_t	weights_degree

int32_t	weights_length

float64_t *	position_weights

int32_t	position_weights_len

float64_t *	weights_buffer

int32_t	mkl_stepsize

int32_t	degree

int32_t	length

int32_t	max_mismatch

int32_t	seq_length

bool	initialized

bool	block_computation

float64_t *	block_weights

EWDKernType	type

int32_t	which_degree

CTrie< DNATrie > *	tries

bool	tree_initialized

CAlphabet *	alphabet

int32_t	cache_size
	cache_size in MB More...

KERNEL_CACHE	kernel_cache
	kernel cache More...

KERNELCACHE_ELEM *	kernel_matrix

CFeatures *	lhs
	feature vectors to occur on left hand side More...

CFeatures *	rhs
	feature vectors to occur on right hand side More...

bool	lhs_equals_rhs
	lhs More...

int32_t	num_lhs
	number of feature vectors on left hand side More...

int32_t	num_rhs
	number of feature vectors on right hand side More...

float64_t	combined_kernel_weight

bool	optimization_initialized

EOptimizationType	opt_type

uint64_t	properties

CKernelNormalizer *	normalizer

Constructor & Destructor Documentation

CWeightedDegreeStringKernel ( )

default constructor

Definition at line 48 of file WeightedDegreeStringKernel.cpp.

CWeightedDegreeStringKernel	(	int32_t	degree,
		EWDKernType	type = `E_WD`
	)

constructor

Parameters

degree	degree
type	weighted degree kernel type

Definition at line 55 of file WeightedDegreeStringKernel.cpp.

CWeightedDegreeStringKernel ( SGVector< float64_t > weights )

constructor

Parameters

weights kernel's weights

Definition at line 68 of file WeightedDegreeStringKernel.cpp.

CWeightedDegreeStringKernel	(	CStringFeatures< char > *	l,
		CStringFeatures< char > *	r,
		int32_t	degree
	)

constructor

Parameters

l	features of left-hand side
r	features of right-hand side
degree	degree

Definition at line 84 of file WeightedDegreeStringKernel.cpp.

~CWeightedDegreeStringKernel ( )

virtual

Definition at line 96 of file WeightedDegreeStringKernel.cpp.

Member Function Documentation

void add_example_to_single_tree	(	int32_t	idx,
		float64_t	weight,
		int32_t	tree_num
	)

protected

add example to single tree

Parameters

idx	index
weight	weight
tree_num	which tree

Definition at line 435 of file WeightedDegreeStringKernel.cpp.

void add_example_to_single_tree_mismatch	(	int32_t	idx,
		float64_t	weight,
		int32_t	tree_num
	)

protected

add example to single tree mismatch

Parameters

idx	index
weight	weight
tree_num	which tree

Definition at line 486 of file WeightedDegreeStringKernel.cpp.

void add_example_to_tree	(	int32_t	idx,
		float64_t	weight
	)

protected

add example to tree

Parameters

idx	index
weight	weight

Definition at line 389 of file WeightedDegreeStringKernel.cpp.

void add_example_to_tree_mismatch	(	int32_t	idx,
		float64_t	weight
	)

protected

add example to tree mismatch

Parameters

idx	index
weight	weight

Definition at line 460 of file WeightedDegreeStringKernel.cpp.

virtual void add_to_normal	(	int32_t	idx,
		float64_t	weight
	)

virtual

add to normal

Parameters

idx	where to add
weight	what to add

Reimplemented from CKernel.

Definition at line 214 of file WeightedDegreeStringKernel.h.

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject * > * dict )

inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters

dict	dictionary of parameters to be built.

Definition at line 597 of file SGObject.cpp.

void cache_kernel_row ( int32_t x )

inherited

cache kernel row

Parameters

x x

Definition at line 302 of file Kernel.cpp.

void cache_multiple_kernel_rows	(	int32_t *	key,
		int32_t	varnum
	)

inherited

cache multiple kernel rows

Parameters

key	key
varnum

Definition at line 376 of file Kernel.cpp.

void cache_reset ( )

inherited

cache reset

Definition at line 602 of file Kernel.h.

void cleanup ( )

virtual

clean up kernel

Reimplemented from CKernel.

Definition at line 182 of file WeightedDegreeStringKernel.cpp.

virtual void clear_normal ( )

virtual

clear normal subkernel functionality

Reimplemented from CKernel.

Definition at line 196 of file WeightedDegreeStringKernel.h.

CSGObject * clone ( )

virtualinherited

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

Returns: an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

Definition at line 714 of file SGObject.cpp.

float64_t compute	(	int32_t	idx_a,
		int32_t	idx_b
	)

protectedvirtual

compute kernel function for features a and b idx_{a,b} denote the index of the feature vectors in the corresponding feature object

Parameters

idx_a	index a
idx_b	index b

Returns: computed kernel function at indices a,b

Implements CKernel.

Definition at line 363 of file WeightedDegreeStringKernel.cpp.

float64_t * compute_abs_weights ( int32_t & len )

compute abs weights

Parameters

len len

Returns: computed abs weights

Definition at line 565 of file WeightedDegreeStringKernel.cpp.

void compute_batch	(	int32_t	num_vec,
		int32_t *	vec_idx,
		float64_t *	target,
		int32_t	num_suppvec,
		int32_t *	IDX,
		float64_t *	alphas,
		float64_t	factor = `1.0`
	)

virtual

compute batch

Parameters

num_vec	number of vectors
vec_idx	vector index
target	target
num_suppvec	number of support vectors
IDX	IDX
alphas	alphas
factor	factor

Reimplemented from CKernel.

Definition at line 862 of file WeightedDegreeStringKernel.cpp.

void * compute_batch_helper ( void * p )

static

helper for compute batch

Parameters

p	thread parameter

Definition at line 826 of file WeightedDegreeStringKernel.cpp.

void compute_by_subkernel	(	int32_t	idx,
		float64_t *	subkernel_contrib
	)

virtual

compute by subkernel

Parameters

idx	index
subkernel_contrib	subkernel contribution

Reimplemented from CKernel.

Definition at line 248 of file WeightedDegreeStringKernel.h.

void compute_by_tree	(	int32_t	idx,
		float64_t *	LevelContrib
	)

compute by tree

Parameters

idx	index
LevelContrib	level contribution

Returns: computed value

Definition at line 538 of file WeightedDegreeStringKernel.cpp.

float64_t compute_by_tree ( int32_t idx )

protected

compute by tree

Parameters

idx index

Returns: computed value

Definition at line 514 of file WeightedDegreeStringKernel.cpp.

virtual float64_t compute_optimized ( int32_t idx )

virtual

compute optimized

Parameters

idx	index to compute

Returns: optimized value at given index

Reimplemented from CKernel.

Definition at line 163 of file WeightedDegreeStringKernel.h.

int32_t compute_row_start	(	int64_t	offs,
		int32_t	n,
		bool	symmetric
	)

protectedinherited

compute row start offset for parallel kernel matrix computation

Parameters

offs	offset
n	number of columns
symmetric	whether matrix is symmetric

Definition at line 919 of file Kernel.h.

float64_t compute_using_block	(	char *	avec,
		int32_t	alen,
		char *	bvec,
		int32_t	blen
	)

protected

compute using block

Parameters

avec	vector a
alen	length of vector a
bvec	vector b
blen	length of vector b

Returns: computed value

Definition at line 290 of file WeightedDegreeStringKernel.cpp.

float64_t compute_with_mismatch	(	char *	avec,
		int32_t	alen,
		char *	bvec,
		int32_t	blen
	)

protected

compute with mismatch

Parameters

avec	vector a
alen	length of vector a
bvec	vector b
blen	length of vector b

Returns: computed value

Definition at line 262 of file WeightedDegreeStringKernel.cpp.

float64_t compute_without_mismatch	(	char *	avec,
		int32_t	alen,
		char *	bvec,
		int32_t	blen
	)

protected

compute without mismatch

Parameters

avec	vector a
alen	length of vector a
bvec	vector b
blen	length of vector b

Returns: computed value

Definition at line 316 of file WeightedDegreeStringKernel.cpp.

float64_t compute_without_mismatch_matrix	(	char *	avec,
		int32_t	alen,
		char *	bvec,
		int32_t	blen
	)

protected

compute without mismatch matrix

Parameters

avec	vector a
alen	length of vector a
bvec	vector b
blen	length of vector b

Returns: computed value

Definition at line 339 of file WeightedDegreeStringKernel.cpp.

void create_empty_tries ( )

protected

create emtpy tries

Definition at line 127 of file WeightedDegreeStringKernel.cpp.

CSGObject * deep_copy ( ) const

virtualinherited

A deep copy. All the instance variables will also be copied.

Definition at line 198 of file SGObject.cpp.

bool delete_optimization ( )

virtual

delete optimization

Returns: if deleting was successful

Reimplemented from CKernel.

Definition at line 248 of file WeightedDegreeStringKernel.cpp.

bool delete_position_weights ( )

delete position weights

Returns: if deleting was successful

Definition at line 521 of file WeightedDegreeStringKernel.h.

bool equals	(	CSGObject *	other,
		float64_t	accuracy = `0.0`,
		bool	tolerant = `false`
	)

virtualinherited

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

Parameters

other	object to compare with
accuracy	accuracy to use for comparison (optional)
tolerant	allows linient check on float equality (within accuracy)

Returns: true if all parameters were equal, false if not

Definition at line 618 of file SGObject.cpp.

int32_t get_activenum_cache ( )

inherited

get activenum cache

Returns: activecnum cache

Definition at line 614 of file Kernel.h.

int32_t get_cache_size ( )

inherited

return the size of the kernel cache

Returns: size of kernel cache

Definition at line 598 of file Kernel.h.

float64_t get_combined_kernel_weight ( )

inherited

get combined kernel weight

Returns: combined kernel weight

Definition at line 802 of file Kernel.h.

int32_t get_degree ( ) const

get degree

Returns: degree

Definition at line 552 of file WeightedDegreeStringKernel.h.

float64_t* get_degree_weights	(	int32_t &	d,
		int32_t &	len
	)

get degree weights

Parameters

d	degree weights will be stored here
len	number of degree weights will be stored here

Definition at line 390 of file WeightedDegreeStringKernel.h.

virtual EFeatureClass get_feature_class ( )

virtualinherited

return feature class the kernel can deal with

Returns: feature class STRING

Implements CKernel.

Definition at line 71 of file StringKernel.h.

virtual EFeatureType get_feature_type ( )

virtualinherited

return feature type the kernel can deal with

Returns: templated feature type

Implements CKernel.

SGIO * get_global_io ( )

inherited

get the io object

Returns: io object

Definition at line 235 of file SGObject.cpp.

Parallel * get_global_parallel ( )

inherited

get the parallel object

Returns: parallel object

Definition at line 277 of file SGObject.cpp.

Version * get_global_version ( )

inherited

get the version object

Returns: version object

Definition at line 290 of file SGObject.cpp.

bool get_is_initialized ( )

inherited

check if optimization is initialized

Returns: if optimization is initialized

Definition at line 753 of file Kernel.h.

virtual SGVector<float64_t> get_kernel_col ( int32_t j )

virtualinherited

get column j

Returns: the jth column of the kernel matrix

Definition at line 262 of file Kernel.h.

SGVector<float64_t> get_kernel_diagonal ( SGVector< float64_t > preallocated = SGVector<float64_t>() )

inherited

Returns: Vector with diagonal elements of the kernel matrix. Note that left- and right-handside features must be set and of equal size

Parameters

preallocated vector with space for results

Definition at line 230 of file Kernel.h.

template SGMatrix< float32_t > get_kernel_matrix< float32_t > ( )

inherited

get kernel matrix

Returns: computed kernel matrix (needs to be cleaned up)

Definition at line 219 of file Kernel.h.

SGMatrix< T > get_kernel_matrix ( )

inherited

get kernel matrix (templated)

Returns: the kernel matrix

Definition at line 1343 of file Kernel.cpp.

template void * get_kernel_matrix_helper< float32_t > ( void * p )

staticprotectedinherited

helper for computing the kernel matrix in a parallel way

Parameters

p	thread parameters

Definition at line 1292 of file Kernel.cpp.

virtual SGVector<float64_t> get_kernel_row ( int32_t i )

virtualinherited

get row i

Returns: the ith row of the kernel matrix

Definition at line 279 of file Kernel.h.

void get_kernel_row	(	int32_t	docnum,
		int32_t *	active2dnum,
		float64_t *	buffer,
		bool	full_line = `false`
	)

inherited

get kernel row

Parameters

docnum	docnum
active2dnum	active2dnum
buffer	buffer
full_line	full line

Definition at line 238 of file Kernel.cpp.

virtual EKernelType get_kernel_type ( )

virtual

return what type of kernel we are

Returns: kernel type WEIGHTEDDEGREE

Implements CStringKernel< char >.

Definition at line 116 of file WeightedDegreeStringKernel.h.

CFeatures* get_lhs ( )

inherited

get left-hand side of features used in kernel

Returns: features of left-hand side

Definition at line 504 of file Kernel.h.

bool get_lhs_equals_rhs ( )

inherited

test whether features on lhs and rhs are the same

Returns: true if features are the same

Definition at line 543 of file Kernel.h.

int32_t get_max_elems_cache ( )

inherited

get maximum elements in cache

Returns: maximum elements in cache

Definition at line 608 of file Kernel.h.

int32_t get_max_mismatch ( ) const

get maximum mismatch

Returns: maximum mismatch

Definition at line 539 of file WeightedDegreeStringKernel.h.

int32_t get_mkl_stepsize ( )

get MKL step size

Returns: MKL step size

Definition at line 588 of file WeightedDegreeStringKernel.h.

SGStringList< char > get_modelsel_names ( )

inherited

Returns: vector of names of all parameters which are registered for model selection

Definition at line 498 of file SGObject.cpp.

char * get_modsel_param_descr ( const char * param_name )

inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

Parameters

param_name name of the parameter

Returns: description of the parameter

Definition at line 522 of file SGObject.cpp.

index_t get_modsel_param_index ( const char * param_name )

inherited

Returns index of model selection parameter with provided index

Parameters

param_name name of model selection parameter

Returns: index of model selection parameter with provided name, -1 if there is no such

Definition at line 535 of file SGObject.cpp.

virtual const char* get_name ( ) const

virtual

return the kernel's name

Returns: name WeightedDegree

Reimplemented from CStringKernel< char >.

Definition at line 122 of file WeightedDegreeStringKernel.h.

CKernelNormalizer * get_normalizer ( )

virtualinherited

obtain the current kernel normalizer

Returns: the kernel normalizer

Definition at line 162 of file Kernel.cpp.

virtual int32_t get_num_subkernels ( )

virtual

get number of subkernels

Returns: number of subkernels

Reimplemented from CKernel.

Definition at line 232 of file WeightedDegreeStringKernel.h.

virtual int32_t get_num_vec_lhs ( )

virtualinherited

get number of vectors of lhs features

Returns: number of vectors of left-hand side

Reimplemented in CCustomKernel.

Definition at line 516 of file Kernel.h.

virtual int32_t get_num_vec_rhs ( )

virtualinherited

get number of vectors of rhs features

Returns: number of vectors of right-hand side

Reimplemented in CCustomKernel.

Definition at line 525 of file Kernel.h.

EOptimizationType get_optimization_type ( )

inherited

get optimization type

Returns: optimization type

Definition at line 741 of file Kernel.h.

virtual SGMatrix<float64_t> get_parameter_gradient	(	const TParameter *	param,
		index_t	index = `-1`
	)

virtualinherited

return derivative with respect to specified parameter

Parameters

param	the parameter
index	the index of the element if parameter is a vector

Returns: gradient with respect to parameter

Reimplemented in CCombinedKernel, CProductKernel, CGaussianKernel, and CPeriodicKernel.

Definition at line 850 of file Kernel.h.

virtual SGVector<float64_t> get_parameter_gradient_diagonal	(	const TParameter *	param,
		index_t	index = `-1`
	)

virtualinherited

return diagonal part of derivative with respect to specified parameter

Parameters

param	the parameter
index	the index of the element if parameter is a vector

Returns: diagonal part of gradient with respect to parameter

Definition at line 864 of file Kernel.h.

float64_t* get_position_weights ( int32_t & len )

get position weights

Parameters

len	number of position weights will be stored here

Returns: position weights

Definition at line 425 of file WeightedDegreeStringKernel.h.

CFeatures* get_rhs ( )

inherited

get right-hand side of features used in kernel

Returns: features of right-hand side

Definition at line 510 of file Kernel.h.

const float64_t* get_subkernel_weights ( int32_t & num_weights )

virtual

get subkernel weights

Parameters

num_weights number of weights will be stored here

Returns: subkernel weights

Reimplemented from CKernel.

Definition at line 270 of file WeightedDegreeStringKernel.h.

SGVector< float64_t > get_subkernel_weights ( )

virtualinherited

get subkernel weights (swig compatible)

Returns: subkernel weights

Reimplemented in CCombinedKernel.

Definition at line 880 of file Kernel.cpp.

EWDKernType get_type ( ) const

get WD kernel weighting type

Returns: weighting type

See also: EWDKernType

Definition at line 107 of file WeightedDegreeStringKernel.h.

bool get_use_block_computation ( )

check if block computation is performed

Returns: if block computation is performed

Definition at line 569 of file WeightedDegreeStringKernel.h.

float64_t* get_weights ( int32_t & num_weights )

get weights

Parameters

num_weights number of weights will be stored here

Returns: weights

Definition at line 402 of file WeightedDegreeStringKernel.h.

int32_t get_which_degree ( )

get which degree

Returns: which degree

Definition at line 605 of file WeightedDegreeStringKernel.h.

virtual bool has_features ( )

virtualinherited

test whether features have been assigned to lhs and rhs

Returns: true if features are assigned

Reimplemented in CCustomKernel, CCombinedKernel, and CProductKernel.

Definition at line 534 of file Kernel.h.

bool has_property ( EKernelProperty p )

inherited

check if kernel has given property

Parameters

p	kernel property

Returns: if kernel has given property

Definition at line 723 of file Kernel.h.

bool init	(	CFeatures *	l,
		CFeatures *	r
	)

virtual

initialize kernel

Parameters

l	features of left-hand side
r	features of right-hand side

Returns: if initializing was successful

Reimplemented from CStringKernel< char >.

Definition at line 140 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights ( )

initialize block weights

Returns: if initialization was successful

Definition at line 801 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_const ( )

initialize block weights constant

Returns: if initialization was successful

Definition at line 725 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_cubicpoly ( )

initialize block weights cubic polynomial

Returns: if initialization was successful

Definition at line 760 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_exp ( )

initialize block weights exponential

Returns: if initialization was successful

Definition at line 773 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_from_wd ( )

initialize block weights from weighted degree

Returns: if initialization was successful

Definition at line 684 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_from_wd_external ( )

initialize block weights from external weighted degree

Returns: if initialization was successful

Definition at line 701 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_linear ( )

initialize block weights linear

Returns: if initialization was successful

Definition at line 735 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_log ( )

initialize block weights logarithmic

Returns: if initialization was successful

Definition at line 787 of file WeightedDegreeStringKernel.cpp.

bool init_block_weights_sqpoly ( )

initialize block weights squared polynomial

Returns: if initialization was successful

Definition at line 746 of file WeightedDegreeStringKernel.cpp.

bool init_normalizer ( )

virtualinherited

initialize the current kernel normalizer

Returns: if init was successful

Definition at line 168 of file Kernel.cpp.

virtual bool init_optimization	(	int32_t	count,
		int32_t *	IDX,
		float64_t *	alphas
	)

virtual

initialize optimization

Parameters

count	count
IDX	index
alphas	alphas

Returns: if initializing was successful

Reimplemented from CKernel.

Definition at line 133 of file WeightedDegreeStringKernel.h.

bool init_optimization	(	int32_t	count,
		int32_t *	IDX,
		float64_t *	alphas,
		int32_t	tree_num
	)

virtual

initialize optimization do initialization for tree_num up to upto_tree, use tree_num=-1 to construct all trees

Parameters

count	count
IDX	IDX
alphas	alphas
tree_num	which tree

Returns: if initializing was successful

Definition at line 206 of file WeightedDegreeStringKernel.cpp.

bool init_optimization_svm ( CSVM * svm )

inherited

initialize optimization

Parameters

svm svm model

Returns: if initializing was successful

Definition at line 910 of file Kernel.cpp.

bool is_generic ( EPrimitiveType * generic ) const

virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

Parameters

generic set to the type of the generic if returning TRUE

Returns: TRUE if a class template.

Definition at line 296 of file SGObject.cpp.

bool is_tree_initialized ( )

check if tree is initialized

Returns: if tree is initialized

Definition at line 383 of file WeightedDegreeStringKernel.h.

float64_t kernel	(	int32_t	idx_a,
		int32_t	idx_b
	)

inherited

get kernel function for lhs feature vector a and rhs feature vector b

Parameters

idx_a	index of feature vector a
idx_b	index of feature vector b

Returns: computed kernel function

Definition at line 206 of file Kernel.h.

int32_t kernel_cache_check ( int32_t cacheidx )

inherited

check if row at given index is cached

Parameters

cacheidx index in cache

Returns: if row at given index is cached

Definition at line 689 of file Kernel.h.

void kernel_cache_cleanup ( )

inherited

cleanup kernel cache

Definition at line 567 of file Kernel.cpp.

void kernel_cache_init	(	int32_t	size,
		bool	regression_hack = `false`
	)

inherited

initialize kernel cache

Parameters

size	size to initialize to
regression_hack	if hack for regression shall be applied

Definition at line 181 of file Kernel.cpp.

void kernel_cache_reset_lru ( )

inherited

kernel cache reset lru

Definition at line 554 of file Kernel.cpp.

void kernel_cache_shrink	(	int32_t	totdoc,
		int32_t	num_shrink,
		int32_t *	after
	)

inherited

kernel cache shrink

Parameters

totdoc	totdoc
num_shrink	number of shrink
after	after

Definition at line 495 of file Kernel.cpp.

int32_t kernel_cache_space_available ( )

inherited

check if there is room for one more row in kernel cache

Returns: if there is room for one more row in kernel cache

Definition at line 698 of file Kernel.h.

int32_t kernel_cache_touch ( int32_t cacheidx )

inherited

update lru time of item at given index to avoid removal from cache

Parameters

cacheidx index in cache

Returns: if updating was successful

Definition at line 674 of file Kernel.h.

void list_kernel ( )

inherited

list kernel

Definition at line 708 of file Kernel.cpp.

void load ( CFile * loader )

inherited

load the kernel matrix

Parameters

loader File object via which to load data

Definition at line 646 of file Kernel.cpp.

bool load_serializable	(	CSerializableFile *	file,
		const char *	prefix = `""`
	)

virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

Parameters

file	where to load from
prefix	prefix for members

Returns: TRUE if done, otherwise FALSE

Definition at line 369 of file SGObject.cpp.

void load_serializable_post	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

Exceptions

ShogunException Will be thrown if an error occurres.

Reimplemented from CSGObject.

Reimplemented in CWeightedDegreePositionStringKernel, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 928 of file Kernel.cpp.

void load_serializable_pre	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

Exceptions

ShogunException will be thrown if an error occurs.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 421 of file SGObject.cpp.

CKernel * obtain_from_generic ( CSGObject * kernel )

staticinherited

Obtains a kernel from a generic SGObject with error checking. Note that if passing NULL, result will be NULL

Parameters

kernel Object to cast to CKernel, is not SG_REFed

Returns: object casted to CKernel, NULL if not possible

Definition at line 896 of file Kernel.cpp.

bool parameter_hash_changed ( )

virtualinherited

Returns: whether parameter combination has changed since last update

Definition at line 262 of file SGObject.cpp.

void print_modsel_params ( )

inherited

prints all parameter registered for model selection and their type

Definition at line 474 of file SGObject.cpp.

void print_serializable ( const char * prefix = "" )

virtualinherited

prints registered parameters out

Parameters

prefix prefix for members

Definition at line 308 of file SGObject.cpp.

void register_params ( )

protectedvirtualinherited

Separate the function of parameter registration This can be the first stage of a general framework for cross-validation or other parameter-based operations

Reimplemented in CSpectrumMismatchRBFKernel, CSNPStringKernel, CANOVAKernel, CSubsequenceStringKernel, CGaussianMatchStringKernel, CGaussianShortRealKernel, CTensorProductPairKernel, CDistanceKernel, and CHistogramIntersectionKernel.

Definition at line 951 of file Kernel.cpp.

void remove_lhs ( )

protectedvirtual

remove lhs from kernel

Reimplemented from CKernel.

Definition at line 116 of file WeightedDegreeStringKernel.cpp.

void remove_lhs_and_rhs ( )

virtualinherited

remove lhs and rhs from kernel

Reimplemented in CCombinedKernel, and CProductKernel.

Definition at line 660 of file Kernel.cpp.

void remove_rhs ( )

virtualinherited

takes all necessary steps if the rhs is removed from kernel

remove rhs from kernel

Reimplemented in CCombinedKernel, CCommUlongStringKernel, and CProductKernel.

Definition at line 693 of file Kernel.cpp.

void resize_kernel_cache	(	KERNELCACHE_IDX	size,
		bool	regression_hack = `false`
	)

inherited

resize kernel cache

Parameters

size	new size
regression_hack	hack for regression

Definition at line 85 of file Kernel.cpp.

SGVector< float64_t > row_col_wise_sum_block	(	index_t	block_begin_row,
		index_t	block_begin_col,
		index_t	block_size_row,
		index_t	block_size_col,
		bool	no_diag = `false`
	)

virtualinherited

Computes row-wise/col-wise sum of kernel values. This method is useful while computing statistical estimation of mean/variance over kernel values but the kernel matrix is too huge to be fit inside memory.

Parameters

block_begin_row	the row index at which the block starts
block_begin_col	the col index at which the block starts
block_size_row	the number of rows in the block
block_size_col	the number of cols in the block

For Example, block_begin_row 0, block_begin_col 4 and block_size_row 5, block_size_col 6 represents the block that starts at index (0,4) in the kernel matrix and goes upto (0+5-1,4+6-1) i.e. (4,9) both inclusive

Parameters

no_diag if true (default is false), the diagonal elements are excluded from the row/col-wise sum, provided that block_size_row and block_size_col are same (i.e. the block is square). Otherwise, these are always added

Returns

a vector whose first block_size_row entries contain row-wise sum of kernel values computed as

\[ v[i]=\sum_{j}k(i+\text{block-begin-row}, j+\text{block-begin-col}) \]

and rest block_size_col entries col-wise sum of kernel values computed as

\[ v[\text{block-size-row}+j]=\sum_{i}k(i+\text{block-begin-row}, j+\text{block-begin-col}) \]

where \(i\in[0,\text{block-size-row}-1]\) and \(j\in[0,\text{block-size-col}-1]\)

Definition at line 1238 of file Kernel.cpp.

SGMatrix< float64_t > row_wise_sum_squared_sum_symmetric_block	(	index_t	block_begin,
		index_t	block_size,
		bool	no_diag = `true`
	)

virtualinherited

Computes row-wise/col-wise sum and squared sum of kernel values from a symmetric part of the kernel matrix that always is supposed to contain the main upper diagonal. This method is useful while computing statistical estimation of mean/variance over kernel values but the kernel matrix is too huge to be fit inside memory.

Parameters

block_begin	the row and col index at which the block starts
block_size	the number of rows and cols in the block

For Example, block_begin 4 and block_size 5 represents the block that starts at index (4,4) in the kernel matrix and goes upto (4+5-1,4+5-1) i.e. (8,8) both inclusive

Parameters

no_diag if true (default), the diagonal elements are excluded from the row/col-wise sum

Returns

a matrix whose first column contains the row-wise sum of kernel values computed as

\[ v_0[i]=\sum_{j}k(i+\text{block-begin}, j+\text{block-begin}) \]

and second column contains the row-wise sum of squared kernel values

\[ v_1[i]=\sum_{j}^k^2(i+\text{block-begin}, j+\text{block-begin}) \]

where \(i,j\in[0,\text{block-size}-1]\)

Definition at line 1179 of file Kernel.cpp.

SGVector< float64_t > row_wise_sum_symmetric_block	(	index_t	block_begin,
		index_t	block_size,
		bool	no_diag = `true`
	)

virtualinherited

Computes row-wise/col-wise sum from a symmetric part of the kernel matrix that always is supposed to contain the main upper diagonal. This method is useful while computing statistical estimation of mean/variance over kernel values but the kernel matrix is too huge to be fit inside memory.

Parameters

block_begin	the row and col index at which the block starts
block_size	the number of rows and cols in the block

For Example, block_begin 4 and block_size 5 represents the block that starts at index (4,4) in the kernel matrix and goes upto (4+5-1,4+5-1) i.e. (8,8) both inclusive

Parameters

no_diag if true (default), the diagonal elements are excluded from the row/col-wise sum

Returns: vector containing row-wise sum computed as
\[ v[i]=\sum_{j}k(i+\text{block-begin}, j+\text{block-begin}) \]
where \(i,j\in[0,\text{block-size}-1]\)

Definition at line 1125 of file Kernel.cpp.

void save ( CFile * writer )

inherited

save kernel matrix

Parameters

writer File object via which to save data

Definition at line 652 of file Kernel.cpp.

bool save_serializable	(	CSerializableFile *	file,
		const char *	prefix = `""`
	)

virtualinherited

Save this object to file.

Parameters

file	where to save the object; will be closed during returning if PREFIX is an empty string.
prefix	prefix for members

Returns: TRUE if done, otherwise FALSE

Definition at line 314 of file SGObject.cpp.

void save_serializable_post	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

Exceptions

ShogunException Will be thrown if an error occurres.

Reimplemented from CSGObject.

Definition at line 943 of file Kernel.cpp.

void save_serializable_pre	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

Exceptions

ShogunException Will be thrown if an error occurres.

Reimplemented from CSGObject.

Definition at line 935 of file Kernel.cpp.

void set_cache_size ( int32_t size )

inherited

set the size of the kernel cache

Parameters

size	of kernel cache

Definition at line 586 of file Kernel.h.

void set_combined_kernel_weight ( float64_t nw )

inherited

set combined kernel weight

Parameters

nw	new combined kernel weight

Definition at line 808 of file Kernel.h.

bool set_degree ( int32_t deg )

set degree

Parameters

deg	new degree

Returns: if setting was successful

Definition at line 546 of file WeightedDegreeStringKernel.h.

void set_generic ( )

inherited

Definition at line 41 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 46 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 51 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 56 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 61 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 66 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 71 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 76 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 81 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 86 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 91 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 96 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 101 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 106 of file SGObject.cpp.

void set_generic ( )

inherited

Definition at line 111 of file SGObject.cpp.

void set_generic ( )

inherited

set generic type to T

void set_global_io ( SGIO * io )

inherited

set the io object

Parameters

io	io object to use

Definition at line 228 of file SGObject.cpp.

void set_global_parallel ( Parallel * parallel )

inherited

set the parallel object

Parameters

parallel parallel object to use

Definition at line 241 of file SGObject.cpp.

void set_global_version ( Version * version )

inherited

set the version object

Parameters

version version object to use

Definition at line 283 of file SGObject.cpp.

void set_is_initialized ( bool p_init )

protectedinherited

set is initialized

Parameters

p_init if optimization shall be set to initialized

Definition at line 899 of file Kernel.h.

bool set_max_mismatch ( int32_t max )

set maximum mismatch

Parameters

max	new maximum mismatch

Returns: if setting was successful

Definition at line 966 of file WeightedDegreeStringKernel.cpp.

bool set_mkl_stepsize ( int32_t step )

set MKL steps ize

Parameters

step	new step size

Returns: if setting was successful

Definition at line 576 of file WeightedDegreeStringKernel.h.

virtual bool set_normalizer ( CKernelNormalizer * normalizer_ )

virtual

set the current kernel normalizer

Returns: if successful

Reimplemented from CKernel.

Definition at line 346 of file WeightedDegreeStringKernel.h.

virtual void set_optimization_type ( EOptimizationType t )

virtualinherited

set optimization type

Parameters

t	optimization type to set

Reimplemented in CCombinedKernel.

Definition at line 747 of file Kernel.h.

bool set_position_weights	(	float64_t *	pws,
		int32_t	len
	)

set position weights

Parameters

pws	new position weights
len	number of position weights

Returns: if setting was successful

Definition at line 654 of file WeightedDegreeStringKernel.cpp.

void set_property ( EKernelProperty p )

protectedinherited

set property

Parameters

p	kernel property to set

Definition at line 881 of file Kernel.h.

virtual void set_subkernel_weights ( SGVector< float64_t > w )

virtual

set subkernel weights

Parameters

w weights

Reimplemented from CKernel.

Definition at line 295 of file WeightedDegreeStringKernel.h.

void set_time ( int32_t t )

inherited

set the lru time

Parameters

t	the time to use

Definition at line 664 of file Kernel.h.

bool set_use_block_computation ( bool block )

set if block computation shall be performed

Parameters

block if block computation shall be performed

Returns: if setting was successful

Definition at line 559 of file WeightedDegreeStringKernel.h.

void set_wd_weights ( SGVector< float64_t > new_weights )

set wd weights

Parameters

new_weights new weights

Definition at line 442 of file WeightedDegreeStringKernel.h.

bool set_wd_weights_by_type ( EWDKernType type )

set wd weights

Parameters

type	weighted degree kernel type

Returns: if setting was successful

if we know a better weighting later on do a switch

Definition at line 571 of file WeightedDegreeStringKernel.cpp.

bool set_weights ( SGMatrix< float64_t > new_weights )

set weights

Parameters

new_weights new weights

Definition at line 624 of file WeightedDegreeStringKernel.cpp.

bool set_which_degree ( int32_t which )

set which degree

Parameters

which which degree

Returns: if setting was successful

Definition at line 595 of file WeightedDegreeStringKernel.h.

CSGObject * shallow_copy ( ) const

virtualinherited

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

Reimplemented in CGaussianKernel.

Definition at line 192 of file SGObject.cpp.

float64_t sum_block	(	index_t	block_begin_row,
		index_t	block_begin_col,
		index_t	block_size_row,
		index_t	block_size_col,
		bool	no_diag = `false`
	)

virtualinherited

Computes sum of kernel values from a specified block. This method is useful while computing statistical estimation of mean/variance over kernel values but the kernel matrix is too huge to be fit inside memory.

Parameters

block_begin_row	the row index at which the block starts
block_begin_col	the col index at which the block starts
block_size_row	the number of rows in the block
block_size_col	the number of cols in the block

For example, block_begin_row 0, block_begin_col 4 and block_size_row 5, block_size_col 6 represents the block that starts at index (0,4) in the kernel matrix and goes upto (0+5-1,4+6-1) i.e. (4,9) both inclusive

Parameters

no_diag if true (default is false), the diagonal elements are excluded from the sum, provided that block_size_row and block_size_col are same (i.e. the block is square). Otherwise, these are always added

Returns: sum of kernel values within the block computed as
\[ \sum_{i}\sum_{j}k(i+\text{block-begin-row}, j+\text{block-begin-col}) \]
where \(i\in[0,\text{block-size-row}-1]\) and \(j\in[0,\text{block-size-col}-1]\)

Definition at line 1079 of file Kernel.cpp.

float64_t sum_symmetric_block	(	index_t	block_begin,
		index_t	block_size,
		bool	no_diag = `true`
	)

virtualinherited

Computes sum from a symmetric part of the kernel matrix that always is supposed to contain the main upper diagonal. This method is useful while computing statistical estimation of mean/variance over kernel values but the kernel matrix is too huge to be fit inside memory.

Parameters

block_begin	the row and col index at which the block starts
block_size	the number of rows and cols in the block

For example, block_begin 4 and block_size 5 represents the block that starts at index (4,4) in the kernel matrix and goes upto (4+5-1,4+5-1) i.e. (8,8) both inclusive

Parameters

no_diag if true (default), the diagonal elements are excluded from the sum

Returns: sum of kernel values within the block computed as
\[ \sum_{i}\sum_{j}k(i+\text{block-begin}, j+\text{block-begin}) \]
where \(i,j\in[0,\text{block-size}-1]\)

Definition at line 1026 of file Kernel.cpp.

void unset_generic ( )

inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 303 of file SGObject.cpp.

void unset_property ( EKernelProperty p )

protectedinherited

unset property

Parameters

p	kernel property to unset

Definition at line 890 of file Kernel.h.

void update_parameter_hash ( )

virtualinherited

Updates the hash of current parameter combination

Definition at line 248 of file SGObject.cpp.

Member Data Documentation

CAlphabet* alphabet

protected

alphabet of features

Definition at line 761 of file WeightedDegreeStringKernel.h.

bool block_computation

protected

if block computation is used

Definition at line 745 of file WeightedDegreeStringKernel.h.

float64_t* block_weights

protected

(internal) block weights

Definition at line 748 of file WeightedDegreeStringKernel.h.

int32_t cache_size

protectedinherited

cache_size in MB

Definition at line 1047 of file Kernel.h.

float64_t combined_kernel_weight

protectedinherited

combined kernel weight

Definition at line 1072 of file Kernel.h.

int32_t degree

protected

degree

Definition at line 732 of file WeightedDegreeStringKernel.h.

bool initialized

protected

if kernel is initialized

Definition at line 742 of file WeightedDegreeStringKernel.h.

SGIO* io

inherited

io

Definition at line 369 of file SGObject.h.

KERNEL_CACHE kernel_cache

protectedinherited

kernel cache

Definition at line 1051 of file Kernel.h.

KERNELCACHE_ELEM* kernel_matrix

protectedinherited

this COULD store the whole kernel matrix usually not applicable / necessary to compute the whole matrix

Definition at line 1056 of file Kernel.h.

int32_t length

protected

length

Definition at line 734 of file WeightedDegreeStringKernel.h.

CFeatures* lhs

protectedinherited

feature vectors to occur on left hand side

Definition at line 1059 of file Kernel.h.

bool lhs_equals_rhs

protectedinherited

lhs

Definition at line 1064 of file Kernel.h.

Parameter* m_gradient_parameters

inherited

parameters wrt which we can compute gradients

Definition at line 384 of file SGObject.h.

uint32_t m_hash

inherited

Hash of parameter values

Definition at line 387 of file SGObject.h.

Parameter* m_model_selection_parameters

inherited

model selection parameters

Definition at line 381 of file SGObject.h.

Parameter* m_parameters

inherited

parameters

Definition at line 378 of file SGObject.h.

int32_t max_mismatch

protected

maximum mismatch

Definition at line 737 of file WeightedDegreeStringKernel.h.

int32_t mkl_stepsize

protected

MKL step size

Definition at line 730 of file WeightedDegreeStringKernel.h.

CKernelNormalizer* normalizer

protectedinherited

normalize the kernel(i,j) function based on this normalization function

Definition at line 1086 of file Kernel.h.

int32_t num_lhs

protectedinherited

number of feature vectors on left hand side

Definition at line 1067 of file Kernel.h.

int32_t num_rhs

protectedinherited

number of feature vectors on right hand side

Definition at line 1069 of file Kernel.h.

EOptimizationType opt_type

protectedinherited

optimization type (currently FASTBUTMEMHUNGRY and SLOWBUTMEMEFFICIENT)

Definition at line 1079 of file Kernel.h.

bool optimization_initialized

protectedinherited

if optimization is initialized

Definition at line 1075 of file Kernel.h.

Parallel* parallel

inherited

parallel

Definition at line 372 of file SGObject.h.

float64_t* position_weights

protected

position weights

Definition at line 724 of file WeightedDegreeStringKernel.h.

int32_t position_weights_len

protected

position weights

Definition at line 726 of file WeightedDegreeStringKernel.h.

uint64_t properties

protectedinherited

kernel properties

Definition at line 1082 of file Kernel.h.

CFeatures* rhs

protectedinherited

feature vectors to occur on right hand side

Definition at line 1061 of file Kernel.h.

int32_t seq_length

protected

sequence length

Definition at line 739 of file WeightedDegreeStringKernel.h.

bool tree_initialized

protected

if tree is initialized

Definition at line 758 of file WeightedDegreeStringKernel.h.

CTrie<DNATrie>* tries

protected

tries

Definition at line 755 of file WeightedDegreeStringKernel.h.

EWDKernType type

protected

WeightedDegree kernel type

Definition at line 750 of file WeightedDegreeStringKernel.h.

Version* version

inherited

version

Definition at line 375 of file SGObject.h.

float64_t* weights

protected

degree*length weights length must match seq_length if != 0

Definition at line 716 of file WeightedDegreeStringKernel.h.

float64_t* weights_buffer

protected

weights buffer

Definition at line 728 of file WeightedDegreeStringKernel.h.

int32_t weights_degree

protected

degree

Definition at line 718 of file WeightedDegreeStringKernel.h.

int32_t weights_length

protected

length

Definition at line 720 of file WeightedDegreeStringKernel.h.

int32_t which_degree

protected

which degree

Definition at line 752 of file WeightedDegreeStringKernel.h.

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

Detailed Description

Public Member Functions

Static Public Member Functions

Public Attributes

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation