Public Member Functions | Static Public Member Functions | Public Attributes | Protected Member Functions | Static Protected Member Functions | Protected Attributes

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 53 of file WeightedDegreeStringKernel.h.

Inheritance diagram for CWeightedDegreeStringKernel:
Inheritance graph
[legend]

List of all members.

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 ()
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 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
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 SGMatrix< float64_t > get_parameter_gradient (TParameter *param, CSGObject *obj, 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 ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=VERSION_PARAMETER)
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=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)
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_parameter_dictionary (CMap< TParameter *, CSGObject * > &dict)

Static Public Member Functions

static void * compute_batch_helper (void *p)

Public Attributes

SGIO * io
Parallel * parallel
Version * version
Parameter * m_parameters
Parameter * m_model_selection_parameters
ParameterMap * m_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 TParameter * migrate (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)
virtual bool update_parameter_hash ()

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
KERNEL_CACHE kernel_cache
 kernel cache
KERNELCACHE_ELEM * kernel_matrix
CFeatures * lhs
 feature vectors to occur on left hand side
CFeatures * rhs
 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
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 212 of file WeightedDegreeStringKernel.h.

void build_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 1201 of file SGObject.cpp.

void cache_kernel_row ( int32_t  x  )  [inherited]

cache kernel row

Parameters:
x x

Definition at line 293 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 367 of file Kernel.cpp.

void cache_reset (  )  [inherited]

cache reset

Definition at line 555 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 194 of file WeightedDegreeStringKernel.h.

float64_t compute ( int32_t  idx_a,
int32_t  idx_b 
) [protected, virtual]

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 246 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 161 of file WeightedDegreeStringKernel.h.

int32_t compute_row_start ( int64_t  offs,
int32_t  n,
bool  symmetric 
) [protected, inherited]

compute row start offset for parallel kernel matrix computation

Parameters:
offs offset
n number of columns
symmetric whether matrix is symmetric

Definition at line 843 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.

virtual CSGObject* deep_copy (  )  const [virtual, inherited]

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

Definition at line 131 of file SGObject.h.

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 519 of file WeightedDegreeStringKernel.h.

int32_t get_activenum_cache (  )  [inherited]

get activenum cache

Returns:
activecnum cache

Definition at line 567 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 551 of file Kernel.h.

float64_t get_combined_kernel_weight (  )  [inherited]

get combined kernel weight

Returns:
combined kernel weight

Definition at line 755 of file Kernel.h.

int32_t get_degree (  )  const

get degree

Returns:
degree

Definition at line 550 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 388 of file WeightedDegreeStringKernel.h.

virtual EFeatureClass get_feature_class (  )  [virtual, inherited]

return feature class the kernel can deal with

Returns:
feature class STRING

Implements CKernel.

Definition at line 69 of file StringKernel.h.

virtual EFeatureType get_feature_type (  )  [virtual, inherited]

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 224 of file SGObject.cpp.

Parallel * get_global_parallel (  )  [inherited]

get the parallel object

Returns:
parallel object

Definition at line 259 of file SGObject.cpp.

Version * get_global_version (  )  [inherited]

get the version object

Returns:
version object

Definition at line 272 of file SGObject.cpp.

bool get_is_initialized (  )  [inherited]

check if optimization is initialized

Returns:
if optimization is initialized

Definition at line 706 of file Kernel.h.

virtual SGVector<float64_t> get_kernel_col ( int32_t  j  )  [virtual, inherited]

get column j

Returns:
the jth column of the kernel matrix

Definition at line 276 of file Kernel.h.

SGVector<float64_t> get_kernel_diagonal (  )  [inherited]
Returns:
Vector with diagonal elements of the kernel matrix. Note that left- and right-handside features must be set and of equal size

Definition at line 250 of file Kernel.h.

SGMatrix<float64_t> get_kernel_matrix (  )  [inherited]

get kernel matrix

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

Definition at line 241 of file Kernel.h.

SGMatrix<T> get_kernel_matrix (  )  [inherited]

get kernel matrix real

Returns:
the kernel matrix

Definition at line 308 of file Kernel.h.

static void* get_kernel_matrix_helper ( void *  p  )  [static, protected, inherited]

helper for computing the kernel matrix in a parallel way

Parameters:
p thread parameters

Definition at line 860 of file Kernel.h.

virtual SGVector<float64_t> get_kernel_row ( int32_t  i  )  [virtual, inherited]

get row i

Returns:
the ith row of the kernel matrix

Definition at line 293 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 229 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 114 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 457 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 496 of file Kernel.h.

int32_t get_max_elems_cache (  )  [inherited]

get maximum elements in cache

Returns:
maximum elements in cache

Definition at line 561 of file Kernel.h.

int32_t get_max_mismatch (  )  const

get maximum mismatch

Returns:
maximum mismatch

Definition at line 537 of file WeightedDegreeStringKernel.h.

int32_t get_mkl_stepsize (  ) 

get MKL step size

Returns:
MKL step size

Definition at line 586 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 1108 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 1132 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 1145 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 120 of file WeightedDegreeStringKernel.h.

CKernelNormalizer * get_normalizer (  )  [virtual, inherited]

obtain the current kernel normalizer

Returns:
the kernel normalizer

Definition at line 153 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 230 of file WeightedDegreeStringKernel.h.

virtual int32_t get_num_vec_lhs (  )  [virtual, inherited]

get number of vectors of lhs features

Returns:
number of vectors of left-hand side

Reimplemented in CCustomKernel.

Definition at line 469 of file Kernel.h.

virtual int32_t get_num_vec_rhs (  )  [virtual, inherited]

get number of vectors of rhs features

Returns:
number of vectors of right-hand side

Reimplemented in CCustomKernel.

Definition at line 478 of file Kernel.h.

EOptimizationType get_optimization_type (  )  [inherited]

get optimization type

Returns:
optimization type

Definition at line 694 of file Kernel.h.

SGMatrix< float64_t > get_parameter_gradient ( TParameter *  param,
CSGObject *  obj,
index_t  index = -1 
) [virtual, inherited]

return derivative with respect to specified parameter

Parameters:
param the parameter
obj the object that owns the parameter
index the index of the element if parameter is a vector
Returns:
gradient with respect to parameter

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

Definition at line 958 of file Kernel.cpp.

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 423 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 463 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 268 of file WeightedDegreeStringKernel.h.

EWDKernType get_type (  )  const

get WD kernel weighting type

Returns:
weighting type
See also:
EWDKernType

Definition at line 105 of file WeightedDegreeStringKernel.h.

bool get_use_block_computation (  ) 

check if block computation is performed

Returns:
if block computation is performed

Definition at line 567 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 400 of file WeightedDegreeStringKernel.h.

int32_t get_which_degree (  ) 

get which degree

Returns:
which degree

Definition at line 603 of file WeightedDegreeStringKernel.h.

virtual bool has_features (  )  [virtual, inherited]

test whether features have been assigned to lhs and rhs

Returns:
true if features are assigned

Reimplemented in CCombinedKernel, CCustomKernel, and CProductKernel.

Definition at line 487 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 676 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 (  )  [virtual, inherited]

initialize the current kernel normalizer

Returns:
if init was successful

Definition at line 159 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 131 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 871 of file Kernel.cpp.

bool is_generic ( EPrimitiveType *  generic  )  const [virtual, inherited]

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 278 of file SGObject.cpp.

bool is_tree_initialized (  ) 

check if tree is initialized

Returns:
if tree is initialized

Definition at line 381 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 228 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 642 of file Kernel.h.

void kernel_cache_cleanup (  )  [inherited]

cleanup kernel cache

Definition at line 555 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 172 of file Kernel.cpp.

void kernel_cache_reset_lru (  )  [inherited]

kernel cache reset lru

Definition at line 542 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 486 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 651 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 627 of file Kernel.h.

void list_kernel (  )  [inherited]

list kernel

Definition at line 696 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 634 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_version parameter version of the file
current_version version from which mapping begins (you want to use VERSION_PARAMETER for this in most cases)
file file to load from
prefix prefix for members
Returns:
(sorted) array of created TParameter instances with file data

Definition at line 679 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_info information of parameter
file_version parameter version of the file, must be <= provided parameter version
file file to load from
prefix prefix for members
Returns:
new array with TParameter instances with the attached data

Definition at line 523 of file SGObject.cpp.

bool load_serializable ( CSerializableFile *  file,
const char *  prefix = "",
int32_t  param_version = VERSION_PARAMETER 
) [virtual, inherited]

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
param_version (optional) a parameter version different to (this is mainly for testing, better do not use)
Returns:
TRUE if done, otherwise FALSE

Reimplemented in CModelSelectionParameters.

Definition at line 354 of file SGObject.cpp.

void load_serializable_post (  )  throw (ShogunException) [protected, virtual, inherited]

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 CANOVAKernel, CCircularKernel, CExponentialKernel, CGaussianKernel, CInverseMultiQuadricKernel, and CWeightedDegreePositionStringKernel.

Definition at line 889 of file Kernel.cpp.

void load_serializable_pre (  )  throw (ShogunException) [protected, virtual, inherited]

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 occurres.

Definition at line 1028 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_base set of TParameter instances that are mapped to the provided target parameter infos
base_version version of the parameter base
target_param_infos set of SGParamInfo instances that specify the target parameter base

Definition at line 717 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo *  target 
) [protected, virtual, inherited]

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_base set of TParameter instances to use for migration
target parameter 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 923 of file SGObject.cpp.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo *  target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
) [protected, virtual, inherited]

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_base set of TParameter instances to use for migration
target parameter info for the resulting TParameter
replacement (used as output) here the TParameter instance which is returned by migration is created into
to_migrate the only source that is used for migration
old_name with this parameter, a name change may be specified

Definition at line 864 of file SGObject.cpp.

void print_modsel_params (  )  [inherited]

prints all parameter registered for model selection and their type

Definition at line 1084 of file SGObject.cpp.

void print_serializable ( const char *  prefix = ""  )  [virtual, inherited]

prints registered parameters out

Parameters:
prefix prefix for members

Definition at line 290 of file SGObject.cpp.

void register_params (  )  [protected, virtual, inherited]

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 CANOVAKernel, CDistanceKernel, CGaussianShortRealKernel, CHistogramIntersectionKernel, CGaussianMatchStringKernel, CRegulatoryModulesStringKernel, CSNPStringKernel, CSpectrumMismatchRBFKernel, and CTensorProductPairKernel.

Definition at line 912 of file Kernel.cpp.

void remove_lhs (  )  [protected, virtual]

remove lhs from kernel

Reimplemented from CKernel.

Definition at line 116 of file WeightedDegreeStringKernel.cpp.

void remove_lhs_and_rhs (  )  [virtual, inherited]

remove lhs and rhs from kernel

Reimplemented in CCombinedKernel, and CProductKernel.

Definition at line 648 of file Kernel.cpp.

void remove_rhs (  )  [virtual, inherited]

takes all necessary steps if the rhs is removed from kernel

remove rhs from kernel

Reimplemented in CCombinedKernel, CProductKernel, and CCommUlongStringKernel.

Definition at line 681 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.

void save ( CFile *  writer  )  [inherited]

save kernel matrix

Parameters:
writer File object via which to save data

Definition at line 640 of file Kernel.cpp.

bool save_serializable ( CSerializableFile *  file,
const char *  prefix = "",
int32_t  param_version = VERSION_PARAMETER 
) [virtual, inherited]

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
param_version (optional) a parameter version different to (this is mainly for testing, better do not use)
Returns:
TRUE if done, otherwise FALSE

Reimplemented in CModelSelectionParameters.

Definition at line 296 of file SGObject.cpp.

void save_serializable_post (  )  throw (ShogunException) [protected, virtual, inherited]

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 904 of file Kernel.cpp.

void save_serializable_pre (  )  throw (ShogunException) [protected, virtual, inherited]

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 896 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 539 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 761 of file Kernel.h.

bool set_degree ( int32_t  deg  ) 

set degree

Parameters:
deg new degree
Returns:
if setting was successful

Definition at line 544 of file WeightedDegreeStringKernel.h.

void set_generic< floatmax_t > (  )  [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 217 of file SGObject.cpp.

void set_global_parallel ( Parallel *  parallel  )  [inherited]

set the parallel object

Parameters:
parallel parallel object to use

Definition at line 230 of file SGObject.cpp.

void set_global_version ( Version *  version  )  [inherited]

set the version object

Parameters:
version version object to use

Definition at line 265 of file SGObject.cpp.

void set_is_initialized ( bool  p_init  )  [protected, inherited]

set is initialized

Parameters:
p_init if optimization shall be set to initialized

Definition at line 823 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 574 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 344 of file WeightedDegreeStringKernel.h.

virtual void set_optimization_type ( EOptimizationType  t  )  [virtual, inherited]

set optimization type

Parameters:
t optimization type to set

Reimplemented in CCombinedKernel.

Definition at line 700 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  )  [protected, inherited]

set property

Parameters:
p kernel property to set

Definition at line 805 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 293 of file WeightedDegreeStringKernel.h.

void set_time ( int32_t  t  )  [inherited]

set the lru time

Parameters:
t the time to use

Definition at line 617 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 557 of file WeightedDegreeStringKernel.h.

void set_wd_weights ( SGVector< float64_t >  new_weights  ) 

set wd weights

Parameters:
new_weights new weights

Definition at line 440 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 593 of file WeightedDegreeStringKernel.h.

virtual CSGObject* shallow_copy (  )  const [virtual, inherited]

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

Reimplemented in CGaussianKernel.

Definition at line 122 of file SGObject.h.

void unset_generic (  )  [inherited]

unset generic type

this has to be called in classes specializing a template class

Definition at line 285 of file SGObject.cpp.

void unset_property ( EKernelProperty  p  )  [protected, inherited]

unset property

Parameters:
p kernel property to unset

Definition at line 814 of file Kernel.h.

bool update_parameter_hash (  )  [protected, virtual, inherited]

Updates the hash of current parameter combination.

Returns:
bool if parameter combination has changed since last update.

Definition at line 237 of file SGObject.cpp.

Member Data Documentation

CAlphabet* alphabet [protected]

alphabet of features

Definition at line 759 of file WeightedDegreeStringKernel.h.

bool block_computation [protected]

if block computation is used

Definition at line 743 of file WeightedDegreeStringKernel.h.

float64_t* block_weights [protected]

(internal) block weights

Definition at line 746 of file WeightedDegreeStringKernel.h.

int32_t cache_size [protected, inherited]

cache_size in MB

Definition at line 1019 of file Kernel.h.

float64_t combined_kernel_weight [protected, inherited]

combined kernel weight

Definition at line 1044 of file Kernel.h.

int32_t degree [protected]

degree

Definition at line 730 of file WeightedDegreeStringKernel.h.

bool initialized [protected]

if kernel is initialized

Definition at line 740 of file WeightedDegreeStringKernel.h.

SGIO* io [inherited]

io

Definition at line 462 of file SGObject.h.

KERNEL_CACHE kernel_cache [protected, inherited]

kernel cache

Definition at line 1023 of file Kernel.h.

KERNELCACHE_ELEM* kernel_matrix [protected, inherited]

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

Reimplemented in CSpectrumMismatchRBFKernel, and CSpectrumRBFKernel.

Definition at line 1028 of file Kernel.h.

int32_t length [protected]

length

Definition at line 732 of file WeightedDegreeStringKernel.h.

CFeatures* lhs [protected, inherited]

feature vectors to occur on left hand side

Definition at line 1031 of file Kernel.h.

bool lhs_equals_rhs [protected, inherited]

lhs

Definition at line 1036 of file Kernel.h.

uint32_t m_hash [inherited]

Hash of parameter values

Definition at line 480 of file SGObject.h.

Parameter* m_model_selection_parameters [inherited]

model selection parameters

Definition at line 474 of file SGObject.h.

ParameterMap* m_parameter_map [inherited]

map for different parameter versions

Definition at line 477 of file SGObject.h.

Parameter* m_parameters [inherited]

parameters

Definition at line 471 of file SGObject.h.

int32_t max_mismatch [protected]

maximum mismatch

Definition at line 735 of file WeightedDegreeStringKernel.h.

int32_t mkl_stepsize [protected]

MKL step size

Definition at line 728 of file WeightedDegreeStringKernel.h.

CKernelNormalizer* normalizer [protected, inherited]

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

Definition at line 1058 of file Kernel.h.

int32_t num_lhs [protected, inherited]

number of feature vectors on left hand side

Definition at line 1039 of file Kernel.h.

int32_t num_rhs [protected, inherited]

number of feature vectors on right hand side

Definition at line 1041 of file Kernel.h.

EOptimizationType opt_type [protected, inherited]

optimization type (currently FASTBUTMEMHUNGRY and SLOWBUTMEMEFFICIENT)

Definition at line 1051 of file Kernel.h.

bool optimization_initialized [protected, inherited]

if optimization is initialized

Definition at line 1047 of file Kernel.h.

Parallel* parallel [inherited]

parallel

Definition at line 465 of file SGObject.h.

float64_t* position_weights [protected]

position weights

Definition at line 722 of file WeightedDegreeStringKernel.h.

int32_t position_weights_len [protected]

position weights

Definition at line 724 of file WeightedDegreeStringKernel.h.

uint64_t properties [protected, inherited]

kernel properties

Definition at line 1054 of file Kernel.h.

CFeatures* rhs [protected, inherited]

feature vectors to occur on right hand side

Definition at line 1033 of file Kernel.h.

int32_t seq_length [protected]

sequence length

Definition at line 737 of file WeightedDegreeStringKernel.h.

bool tree_initialized [protected]

if tree is initialized

Definition at line 756 of file WeightedDegreeStringKernel.h.

CTrie<DNATrie>* tries [protected]

tries

Definition at line 753 of file WeightedDegreeStringKernel.h.

EWDKernType type [protected]

WeightedDegree kernel type

Definition at line 748 of file WeightedDegreeStringKernel.h.

Version* version [inherited]

version

Definition at line 468 of file SGObject.h.

float64_t* weights [protected]

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

Definition at line 714 of file WeightedDegreeStringKernel.h.

float64_t* weights_buffer [protected]

weights buffer

Definition at line 726 of file WeightedDegreeStringKernel.h.

int32_t weights_degree [protected]

degree

Definition at line 716 of file WeightedDegreeStringKernel.h.

int32_t weights_length [protected]

length

Definition at line 718 of file WeightedDegreeStringKernel.h.

int32_t which_degree [protected]

which degree

Definition at line 750 of file WeightedDegreeStringKernel.h.

The documentation for this class was generated from the following files:
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines
SHOGUN Machine Learning Toolbox - Documentation