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CWeightedDegreeStringKernel Class Reference

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:
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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_tget_subkernel_weights (int32_t &num_weights)
virtual void set_subkernel_weights (SGVector< float64_t > w)
virtual bool set_normalizer (CKernelNormalizer *normalizer_)
float64_tcompute_abs_weights (int32_t &len)
void compute_by_tree (int32_t idx, float64_t *LevelContrib)
bool is_tree_initialized ()
float64_tget_degree_weights (int32_t &d, int32_t &len)
float64_tget_weights (int32_t &num_weights)
float64_tget_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_tget_kernel_matrix ()
template<class T >
SGMatrix< T > get_kernel_matrix ()
SGVector< float64_tget_kernel_diagonal (SGVector< float64_t > preallocated=SGVector< float64_t >())
virtual SGVector< float64_tget_kernel_col (int32_t j)
virtual SGVector< float64_tget_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_trow_wise_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true)
virtual SGMatrix< float64_trow_wise_sum_squared_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true)
virtual SGVector< float64_trow_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 CKernelNormalizerget_normalizer ()
virtual bool init_normalizer ()
void load (CFile *loader)
void save (CFile *writer)
CFeaturesget_lhs ()
CFeaturesget_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
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_tget_subkernel_weights ()
virtual SGMatrix< float64_tget_parameter_gradient (const TParameter *param, index_t index=-1)
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_copy () const
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_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 CSGObjectclone ()

Static Public Member Functions

static void * compute_batch_helper (void *p)
static CKernelobtain_from_generic (CSGObject *kernel)

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
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 TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)
virtual void one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL)
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_tweights
int32_t weights_degree
int32_t weights_length
float64_tposition_weights
int32_t position_weights_len
float64_tweights_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_tblock_weights
EWDKernType type
int32_t which_degree
CTrie< DNATrie > * tries
bool tree_initialized
CAlphabetalphabet
int32_t cache_size
 cache_size in MB
KERNEL_CACHE kernel_cache
 kernel cache
KERNELCACHE_ELEMkernel_matrix
CFeatureslhs
 feature vectors to occur on left hand side
CFeaturesrhs
 feature vectors to occur on right hand side
bool lhs_equals_rhs
 lhs
int32_t num_lhs
 number of feature vectors on left hand side
int32_t num_rhs
 number of feature vectors on right hand side
float64_t combined_kernel_weight
bool optimization_initialized
EOptimizationType opt_type
uint64_t properties
CKernelNormalizernormalizer

Constructor & Destructor Documentation

default constructor

Definition at line 48 of file WeightedDegreeStringKernel.cpp.

CWeightedDegreeStringKernel ( int32_t  degree,
EWDKernType  type = E_WD 
)

constructor

Parameters
degreedegree
typeweighted degree kernel type

Definition at line 55 of file WeightedDegreeStringKernel.cpp.

constructor

Parameters
weightskernel's weights

Definition at line 68 of file WeightedDegreeStringKernel.cpp.

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

constructor

Parameters
lfeatures of left-hand side
rfeatures of right-hand side
degreedegree

Definition at line 84 of file WeightedDegreeStringKernel.cpp.

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
idxindex
weightweight
tree_numwhich 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
idxindex
weightweight
tree_numwhich 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
idxindex
weightweight

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
idxindex
weightweight

Definition at line 460 of file WeightedDegreeStringKernel.cpp.

virtual void add_to_normal ( int32_t  idx,
float64_t  weight 
)
virtual

add to normal

Parameters
idxwhere to add
weightwhat 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
dictdictionary of parameters to be built.

Definition at line 1185 of file SGObject.cpp.

void cache_kernel_row ( int32_t  x)
inherited

cache kernel row

Parameters
xx

Definition at line 291 of file Kernel.cpp.

void cache_multiple_kernel_rows ( int32_t *  key,
int32_t  varnum 
)
inherited

cache multiple kernel rows

Parameters
keykey
varnum

Definition at line 365 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 1302 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_aindex a
idx_bindex 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
lenlen
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_vecnumber of vectors
vec_idxvector index
targettarget
num_suppvecnumber of support vectors
IDXIDX
alphasalphas
factorfactor

Reimplemented from CKernel.

Definition at line 862 of file WeightedDegreeStringKernel.cpp.

void * compute_batch_helper ( void *  p)
static

helper for compute batch

Parameters
pthread 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
idxindex
subkernel_contribsubkernel 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
idxindex
LevelContriblevel 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
idxindex
Returns
computed value

Definition at line 514 of file WeightedDegreeStringKernel.cpp.

virtual float64_t compute_optimized ( int32_t  idx)
virtual

compute optimized

Parameters
idxindex 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
offsoffset
nnumber of columns
symmetricwhether matrix is symmetric

Definition at line 906 of file Kernel.h.

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

compute using block

Parameters
avecvector a
alenlength of vector a
bvecvector b
blenlength 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
avecvector a
alenlength of vector a
bvecvector b
blenlength 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
avecvector a
alenlength of vector a
bvecvector b
blenlength 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
avecvector a
alenlength of vector a
bvecvector b
blenlength 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 146 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
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 1206 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
ddegree weights will be stored here
lennumber 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 183 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 224 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 237 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
preallocatedvector with space for results

Definition at line 228 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 217 of file Kernel.h.

SGMatrix<T> get_kernel_matrix ( )
inherited

get kernel matrix (templated)

Returns
the kernel matrix
template void * get_kernel_matrix_helper< float32_t > ( void *  p)
staticprotectedinherited

helper for computing the kernel matrix in a parallel way

Parameters
pthread parameters

Definition at line 1278 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
docnumdocnum
active2dnumactive2dnum
bufferbuffer
full_linefull line

Definition at line 227 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 1077 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_namename of the parameter
Returns
description of the parameter

Definition at line 1101 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_namename of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1114 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 151 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
paramthe parameter
indexthe index of the element if parameter is a vector
Returns
gradient with respect to parameter

Reimplemented in CCombinedKernel, CProductKernel, CGaussianKernel, CLinearARDKernel, and CGaussianARDKernel.

Definition at line 850 of file Kernel.h.

float64_t* get_position_weights ( int32_t &  len)

get position weights

Parameters
lennumber 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_weightsnumber 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 866 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_weightsnumber 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
pkernel 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
lfeatures of left-hand side
rfeatures 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 157 of file Kernel.cpp.

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

initialize optimization

Parameters
countcount
IDXindex
alphasalphas
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
countcount
IDXIDX
alphasalphas
tree_numwhich tree
Returns
if initializing was successful

Definition at line 206 of file WeightedDegreeStringKernel.cpp.

bool init_optimization_svm ( CSVM svm)
inherited

initialize optimization

Parameters
svmsvm model
Returns
if initializing was successful

Definition at line 896 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
genericset to the type of the generic if returning TRUE
Returns
TRUE if a class template.

Definition at line 243 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_aindex of feature vector a
idx_bindex of feature vector b
Returns
computed kernel function

Definition at line 204 of file Kernel.h.

int32_t kernel_cache_check ( int32_t  cacheidx)
inherited

check if row at given index is cached

Parameters
cacheidxindex 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 556 of file Kernel.cpp.

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

initialize kernel cache

Parameters
sizesize to initialize to
regression_hackif hack for regression shall be applied

Definition at line 170 of file Kernel.cpp.

void kernel_cache_reset_lru ( )
inherited

kernel cache reset lru

Definition at line 543 of file Kernel.cpp.

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

kernel cache shrink

Parameters
totdoctotdoc
num_shrinknumber of shrink
afterafter

Definition at line 484 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
cacheidxindex in cache
Returns
if updating was successful

Definition at line 674 of file Kernel.h.

void list_kernel ( )
inherited

list kernel

Definition at line 697 of file Kernel.cpp.

void load ( CFile loader)
inherited

load the kernel matrix

Parameters
loaderFile object via which to load data

Definition at line 635 of file Kernel.cpp.

DynArray< TParameter * > * load_all_file_parameters ( int32_t  file_version,
int32_t  current_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

Parameters
file_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
Returns
(sorted) array of created TParameter instances with file data

Definition at line 648 of file SGObject.cpp.

DynArray< TParameter * > * load_file_parameters ( const SGParamInfo param_info,
int32_t  file_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

Parameters
param_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
Returns
new array with TParameter instances with the attached data

Definition at line 489 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
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
filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 320 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
ShogunExceptionWill be thrown if an error occurres.

Reimplemented from CSGObject.

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

Definition at line 914 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
ShogunExceptionWill be thrown if an error occurres.

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

Definition at line 999 of file SGObject.cpp.

void map_parameters ( DynArray< TParameter * > *  param_base,
int32_t &  base_version,
DynArray< const SGParamInfo * > *  target_param_infos 
)
inherited

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

Parameters
param_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

Definition at line 686 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
)
protectedvirtualinherited

creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.

If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass

Parameters
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
Returns
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

Definition at line 893 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
kernelObject to cast to CKernel, is not SG_REFed
Returns
object casted to CKernel, NULL if not possible

Definition at line 882 of file Kernel.cpp.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
)
protectedvirtualinherited

This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)

Parameters
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

Definition at line 833 of file SGObject.cpp.

bool parameter_hash_changed ( )
virtualinherited
Returns
whether parameter combination has changed since last update

Definition at line 209 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1053 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 255 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 937 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 649 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 682 of file Kernel.cpp.

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

resize kernel cache

Parameters
sizenew size
regression_hackhack 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_rowthe row index at which the block starts
block_begin_colthe col index at which the block starts
block_size_rowthe number of rows in the block
block_size_colthe 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_diagif 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 1224 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_beginthe row and col index at which the block starts
block_sizethe 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_diagif 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 1165 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_beginthe row and col index at which the block starts
block_sizethe 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_diagif 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 1111 of file Kernel.cpp.

void save ( CFile writer)
inherited

save kernel matrix

Parameters
writerFile object via which to save data

Definition at line 641 of file Kernel.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Save this object to file.

Parameters
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 261 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
ShogunExceptionWill be thrown if an error occurres.

Reimplemented from CSGObject.

Definition at line 929 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
ShogunExceptionWill be thrown if an error occurres.

Reimplemented from CSGObject.

Definition at line 921 of file Kernel.cpp.

void set_cache_size ( int32_t  size)
inherited

set the size of the kernel cache

Parameters
sizeof kernel cache

Definition at line 586 of file Kernel.h.

void set_combined_kernel_weight ( float64_t  nw)
inherited

set combined kernel weight

Parameters
nwnew combined kernel weight

Definition at line 808 of file Kernel.h.

bool set_degree ( int32_t  deg)

set degree

Parameters
degnew degree
Returns
if setting was successful

Definition at line 546 of file WeightedDegreeStringKernel.h.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 38 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 176 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 189 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 230 of file SGObject.cpp.

void set_is_initialized ( bool  p_init)
protectedinherited

set is initialized

Parameters
p_initif optimization shall be set to initialized

Definition at line 886 of file Kernel.h.

bool set_max_mismatch ( int32_t  max)

set maximum mismatch

Parameters
maxnew 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
stepnew 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
toptimization 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
pwsnew position weights
lennumber 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
pkernel property to set

Definition at line 868 of file Kernel.h.

virtual void set_subkernel_weights ( SGVector< float64_t w)
virtual

set subkernel weights

Parameters
wweights

Reimplemented from CKernel.

Definition at line 295 of file WeightedDegreeStringKernel.h.

void set_time ( int32_t  t)
inherited

set the lru time

Parameters
tthe 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
blockif 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_weightsnew weights

Definition at line 442 of file WeightedDegreeStringKernel.h.

bool set_wd_weights_by_type ( EWDKernType  type)

set wd weights

Parameters
typeweighted 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_weightsnew weights

Definition at line 624 of file WeightedDegreeStringKernel.cpp.

bool set_which_degree ( int32_t  which)

set which degree

Parameters
whichwhich 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 140 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_rowthe row index at which the block starts
block_begin_colthe col index at which the block starts
block_size_rowthe number of rows in the block
block_size_colthe 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_diagif 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 1065 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_beginthe row and col index at which the block starts
block_sizethe 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_diagif 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 1012 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 250 of file SGObject.cpp.

void unset_property ( EKernelProperty  p)
protectedinherited

unset property

Parameters
pkernel property to unset

Definition at line 877 of file Kernel.h.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 196 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 1034 of file Kernel.h.

float64_t combined_kernel_weight
protectedinherited

combined kernel weight

Definition at line 1059 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 461 of file SGObject.h.

KERNEL_CACHE kernel_cache
protectedinherited

kernel cache

Definition at line 1038 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 1043 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 1046 of file Kernel.h.

bool lhs_equals_rhs
protectedinherited

lhs

Definition at line 1051 of file Kernel.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 476 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 482 of file SGObject.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 473 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 479 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 470 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 1073 of file Kernel.h.

int32_t num_lhs
protectedinherited

number of feature vectors on left hand side

Definition at line 1054 of file Kernel.h.

int32_t num_rhs
protectedinherited

number of feature vectors on right hand side

Definition at line 1056 of file Kernel.h.

EOptimizationType opt_type
protectedinherited

optimization type (currently FASTBUTMEMHUNGRY and SLOWBUTMEMEFFICIENT)

Definition at line 1066 of file Kernel.h.

bool optimization_initialized
protectedinherited

if optimization is initialized

Definition at line 1062 of file Kernel.h.

Parallel* parallel
inherited

parallel

Definition at line 464 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 1069 of file Kernel.h.

CFeatures* rhs
protectedinherited

feature vectors to occur on right hand side

Definition at line 1048 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 467 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:

SHOGUN Machine Learning Toolbox - Documentation