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CGaussianARDSparseKernel Class Reference

Detailed Description

Gaussian Kernel with Automatic Relevance Detection with supporting Sparse inference.

This kernel supports to compute the gradient wrt latent features (inducing points), which are not hyper-parameters of the kernel.

Definition at line 50 of file GaussianARDSparseKernel.h.

Inheritance diagram for CGaussianARDSparseKernel:
[legend]

Public Member Functions

 CGaussianARDSparseKernel ()
 
virtual EKernelType get_kernel_type ()
 
virtual const char * get_name () const
 
virtual ~CGaussianARDSparseKernel ()
 
 CGaussianARDSparseKernel (int32_t size)
 
 CGaussianARDSparseKernel (CDotFeatures *l, CDotFeatures *r, int32_t size=10)
 
virtual SGMatrix< float64_tget_parameter_gradient (const TParameter *param, index_t index=-1)
 
virtual SGVector< float64_tget_parameter_gradient_diagonal (const TParameter *param, index_t index=-1)
 
virtual bool init (CFeatures *l, CFeatures *r)
 
virtual EFeatureClass get_feature_class ()
 
virtual EFeatureType get_feature_type ()
 
virtual SGMatrix< float64_tget_weights ()
 
virtual void set_scalar_weights (float64_t weight)
 
virtual void set_vector_weights (SGVector< float64_t > weights)
 
virtual void set_matrix_weights (SGMatrix< float64_t > weights)
 
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 bool set_normalizer (CKernelNormalizer *normalizer)
 
virtual CKernelNormalizerget_normalizer ()
 
virtual bool init_normalizer ()
 
virtual void cleanup ()
 
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_lhs ()
 
virtual void remove_rhs ()
 takes all necessary steps if the rhs is removed from kernel More...
 
void set_cache_size (int32_t size)
 
int32_t get_cache_size ()
 
void cache_reset ()
 
int32_t get_max_elems_cache ()
 
int32_t get_activenum_cache ()
 
void cache_kernel_row (int32_t x)
 
void cache_multiple_kernel_rows (int32_t *key, int32_t varnum)
 
void kernel_cache_reset_lru ()
 
void kernel_cache_shrink (int32_t totdoc, int32_t num_shrink, int32_t *after)
 
void resize_kernel_cache (KERNELCACHE_IDX size, bool regression_hack=false)
 
void set_time (int32_t t)
 
int32_t kernel_cache_touch (int32_t cacheidx)
 
int32_t kernel_cache_check (int32_t cacheidx)
 
int32_t kernel_cache_space_available ()
 
void kernel_cache_init (int32_t size, bool regression_hack=false)
 
void kernel_cache_cleanup ()
 
void list_kernel ()
 
bool has_property (EKernelProperty p)
 
virtual void clear_normal ()
 
virtual void add_to_normal (int32_t vector_idx, float64_t weight)
 
EOptimizationType get_optimization_type ()
 
virtual void set_optimization_type (EOptimizationType t)
 
bool get_is_initialized ()
 
virtual bool init_optimization (int32_t count, int32_t *IDX, float64_t *weights)
 
virtual bool delete_optimization ()
 
bool init_optimization_svm (CSVM *svm)
 
virtual float64_t compute_optimized (int32_t vector_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)
 
float64_t get_combined_kernel_weight ()
 
void set_combined_kernel_weight (float64_t nw)
 
virtual int32_t get_num_subkernels ()
 
virtual void compute_by_subkernel (int32_t vector_idx, float64_t *subkernel_contrib)
 
virtual const float64_tget_subkernel_weights (int32_t &num_weights)
 
virtual SGVector< float64_tget_subkernel_weights ()
 
virtual void set_subkernel_weights (SGVector< float64_t > weights)
 
virtual CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
 
void set_global_io (SGIO *io)
 
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)
 
bool has (const std::string &name) const
 
template<typename T >
bool has (const Tag< T > &tag) const
 
template<typename T , typename U = void>
bool has (const std::string &name) const
 
template<typename T >
void set (const Tag< T > &_tag, const T &value)
 
template<typename T , typename U = void>
void set (const std::string &name, const T &value)
 
template<typename T >
get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
get (const std::string &name) const
 
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 CGaussianARDSparseKernelobtain_from_generic (CKernel *kernel)
 
static CKernelobtain_from_generic (CSGObject *kernel)
 

Public Attributes

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

virtual float64_t distance (int32_t idx_a, int32_t idx_b)
 
virtual void precompute_squared ()
 
virtual SGVector< float64_tprecompute_squared_helper (CDotFeatures *df)
 
virtual float64_t compute_helper (SGVector< float64_t > avec, SGVector< float64_t >bvec)
 
virtual float64_t compute_gradient_helper (SGVector< float64_t > avec, SGVector< float64_t > bvec, float64_t scale, index_t index)
 
virtual float64_t get_parameter_gradient_helper (const TParameter *param, index_t index, int32_t idx_a, int32_t idx_b, SGVector< float64_t > avec, SGVector< float64_t > bvec)
 
virtual SGVector< float64_tget_feature_vector (int32_t idx, CFeatures *hs)
 
virtual float64_t compute (int32_t idx_a, int32_t idx_b)
 
virtual void set_weights (SGMatrix< float64_t > weights)
 
void lazy_update_weights ()
 
SGMatrix< float64_tget_weighted_vector (SGVector< float64_t > vec)
 
virtual SGMatrix< float64_tcompute_right_product (SGVector< float64_t >vec, float64_t &scalar_weight)
 
virtual void check_weight_gradient_index (index_t index)
 
void set_property (EKernelProperty p)
 
void unset_property (EKernelProperty p)
 
void set_is_initialized (bool p_init)
 
int32_t compute_row_start (int64_t offs, int32_t n, bool symmetric)
 
virtual void load_serializable_post () throw (ShogunException)
 
virtual void save_serializable_pre () throw (ShogunException)
 
virtual void save_serializable_post () throw (ShogunException)
 
virtual void register_params ()
 
virtual void load_serializable_pre () throw (ShogunException)
 
template<typename T >
void register_param (Tag< T > &_tag, const T &value)
 
template<typename T >
void register_param (const std::string &name, const T &value)
 
bool clone_parameters (CSGObject *other)
 

Static Protected Member Functions

template<class T >
static void * get_kernel_matrix_helper (void *p)
 

Protected Attributes

SGVector< float64_tm_sq_lhs
 
SGVector< float64_tm_sq_rhs
 
SGMatrix< float64_tm_weights_raw
 
SGVector< float64_tm_log_weights
 
index_t m_weights_rows
 
index_t m_weights_cols
 
EARDKernelType m_ARD_type
 
int32_t cache_size
 cache_size in MB More...
 
KERNEL_CACHE kernel_cache
 kernel cache More...
 
KERNELCACHE_ELEMkernel_matrix
 
CFeatureslhs
 feature vectors to occur on left hand side More...
 
CFeaturesrhs
 feature vectors to occur on right hand side More...
 
bool lhs_equals_rhs
 lhs More...
 
int32_t num_lhs
 number of feature vectors on left hand side More...
 
int32_t num_rhs
 number of feature vectors on right hand side More...
 
float64_t combined_kernel_weight
 
bool optimization_initialized
 
EOptimizationType opt_type
 
uint64_t properties
 
CKernelNormalizernormalizer
 

Constructor & Destructor Documentation

default constructor

Definition at line 37 of file GaussianARDSparseKernel.cpp.

destructor

Definition at line 45 of file GaussianARDSparseKernel.cpp.

CGaussianARDSparseKernel ( int32_t  size)

constructor

Parameters
sizecache size

Definition at line 51 of file GaussianARDSparseKernel.cpp.

CGaussianARDSparseKernel ( CDotFeatures l,
CDotFeatures r,
int32_t  size = 10 
)

constructor

Parameters
lfeatures of left-hand side
rfeatures of right-hand side
sizecache size

Definition at line 57 of file GaussianARDSparseKernel.cpp.

Member Function Documentation

void add_to_normal ( int32_t  vector_idx,
float64_t  weight 
)
virtualinherited

add vector*factor to 'virtual' normal vector

Parameters
vector_idxindex
weightweight

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommUlongStringKernel, CCommWordStringKernel, CLinearKernel, CLinearStringKernel, and CWeightedCommWordStringKernel.

Definition at line 829 of file Kernel.cpp.

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 630 of file SGObject.cpp.

void cache_kernel_row ( int32_t  x)
inherited

cache kernel row

Parameters
xx

Definition at line 300 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 374 of file Kernel.cpp.

void cache_reset ( )
inherited

cache reset

Definition at line 603 of file kernel/Kernel.h.

void check_weight_gradient_index ( index_t  index)
protectedvirtualinherited

check whether index of gradient wrt weights is valid

Parameters
indexthe index of the element if parameter is a vector or matrix if the parameter is a matrix, index is the linearized index of the matrix (column-major)

Definition at line 267 of file ExponentialARDKernel.cpp.

void cleanup ( )
virtualinherited
void clear_normal ( )
virtualinherited

for optimizable kernels, i.e. kernels where the weight vector can be computed explicitly (if it fits into memory)

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommUlongStringKernel, CCommWordStringKernel, CLinearKernel, and CLinearStringKernel.

Definition at line 834 of file Kernel.cpp.

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

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

Definition at line 729 of file SGObject.cpp.

bool clone_parameters ( CSGObject other)
protectedinherited

Definition at line 754 of file SGObject.cpp.

virtual float64_t compute ( int32_t  idx_a,
int32_t  idx_b 
)
protectedvirtualinherited

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 kernel(idx_a, idx_b)=exp(-distance(idx_a, idx_b))

Reimplemented from CDotKernel.

Definition at line 148 of file ExponentialARDKernel.h.

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 
)
virtualinherited

computes output for a batch of examples in an optimized fashion (favorable if kernel supports it, i.e. has KP_BATCHEVALUATION. to the outputvector target (of length num_vec elements) the output for the examples enumerated in vec_idx are added. therefore make sure that it is initialized with ZERO. the following num_suppvec, IDX, alphas arguments are the number of support vectors, their indices and weights

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.

Definition at line 822 of file Kernel.cpp.

void compute_by_subkernel ( int32_t  vector_idx,
float64_t subkernel_contrib 
)
virtualinherited

compute by subkernel

Parameters
vector_idxindex
subkernel_contribsubkernel contribution

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.

Definition at line 844 of file Kernel.cpp.

float64_t compute_gradient_helper ( SGVector< float64_t avec,
SGVector< float64_t bvec,
float64_t  scale,
index_t  index 
)
protectedvirtualinherited

helper function used to compute derivative with respect to weights

Parameters
avecleft feature vector
bvecright feature vector
scalescaling value
indexthe linearized index of a weight matrix (column-major)
Returns
gradient with respect to parameter

Definition at line 140 of file GaussianARDKernel.cpp.

float64_t compute_helper ( SGVector< float64_t avec,
SGVector< float64_t bvec 
)
protectedvirtualinherited

helper function used to compute kernel function for features avec and bvec

Parameters
avecleft feature vector
bvecright feature vector
Returns
computed kernel value

Definition at line 118 of file GaussianARDKernel.cpp.

float64_t compute_optimized ( int32_t  vector_idx)
virtualinherited

compute optimized

Parameters
vector_idxindex to compute
Returns
optimized value at given index

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommWordStringKernel, CCommUlongStringKernel, CLinearKernel, CLinearStringKernel, and CWeightedCommWordStringKernel.

Definition at line 816 of file Kernel.cpp.

SGMatrix< float64_t > compute_right_product ( SGVector< float64_t vec,
float64_t scalar_weight 
)
protectedvirtualinherited

helper function used to compute kernel value

The function is to compute for scalar weights: \(V=\textbf{vec}\) and scalar_weight= \(\lambda\) for vector weights: \(V=\lambda .* \textbf{vec}\) for matrix weights: \(V=\Lambda^T * \textbf{vec}\)

Parameters
vecfeature vector
scalar_weightset the scaling value, which is used in the scalar case (first case).
Returns
the result of \(V\)

Definition at line 248 of file ExponentialARDKernel.cpp.

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 920 of file kernel/Kernel.h.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 231 of file SGObject.cpp.

bool delete_optimization ( )
virtualinherited

delete optimization

Returns
if deleting was successful

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommWordStringKernel, CCommUlongStringKernel, CLinearKernel, and CLinearStringKernel.

Definition at line 810 of file Kernel.cpp.

float64_t distance ( int32_t  idx_a,
int32_t  idx_b 
)
protectedvirtualinherited

compute the distance between 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 the distance

Note that in GaussianARDKernel, kernel(idx_a, idx_b)=exp(-distance(idx_a, idx_b))

Implements CExponentialARDKernel.

Definition at line 36 of file GaussianARDKernel.cpp.

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 651 of file SGObject.cpp.

T get ( const Tag< T > &  _tag) const
inherited

Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
Returns
value of the parameter identified by the input tag

Definition at line 376 of file SGObject.h.

T get ( const std::string &  name) const
inherited

Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
Returns
value of the parameter corresponding to the input name and type

Definition at line 399 of file SGObject.h.

int32_t get_activenum_cache ( )
inherited

get activenum cache

Returns
activecnum cache

Definition at line 615 of file kernel/Kernel.h.

int32_t get_cache_size ( )
inherited

return the size of the kernel cache

Returns
size of kernel cache

Definition at line 599 of file kernel/Kernel.h.

float64_t get_combined_kernel_weight ( )
inherited

get combined kernel weight

Returns
combined kernel weight

Definition at line 803 of file kernel/Kernel.h.

virtual EFeatureClass get_feature_class ( )
virtualinherited

return feature class the kernel can deal with

Returns
feature class DENSE

Reimplemented from CDotKernel.

Definition at line 93 of file ExponentialARDKernel.h.

virtual EFeatureType get_feature_type ( )
virtualinherited

return feature type the kernel can deal with

Returns
float64_t feature type

Reimplemented from CDotKernel.

Definition at line 99 of file ExponentialARDKernel.h.

SGVector< float64_t > get_feature_vector ( int32_t  idx,
CFeatures hs 
)
protectedvirtualinherited

get features vector given idx

Parameters
idxindex of CFeatures
hsfeatures
Returns
the features vector

Definition at line 54 of file ExponentialARDKernel.cpp.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 268 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 310 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 323 of file SGObject.cpp.

bool get_is_initialized ( )
inherited

check if optimization is initialized

Returns
if optimization is initialized

Definition at line 754 of file kernel/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 263 of file kernel/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 231 of file kernel/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 220 of file kernel/Kernel.h.

SGMatrix< T > get_kernel_matrix ( )
inherited

get kernel matrix (templated)

Returns
the kernel matrix

Definition at line 1316 of file Kernel.cpp.

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

helper for computing the kernel matrix in a parallel way

Parameters
pthread parameters

Definition at line 1265 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 280 of file kernel/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 236 of file Kernel.cpp.

virtual EKernelType get_kernel_type ( )
virtual

return what type of kernel we are

Returns
kernel type GAUSSIANARD

Reimplemented from CGaussianARDKernel.

Definition at line 60 of file GaussianARDSparseKernel.h.

CFeatures* get_lhs ( )
inherited

get left-hand side of features used in kernel

Returns
features of left-hand side

Definition at line 505 of file kernel/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 544 of file kernel/Kernel.h.

int32_t get_max_elems_cache ( )
inherited

get maximum elements in cache

Returns
maximum elements in cache

Definition at line 609 of file kernel/Kernel.h.

SGStringList< char > get_modelsel_names ( )
inherited
Returns
vector of names of all parameters which are registered for model selection

Definition at line 531 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 555 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 568 of file SGObject.cpp.

virtual const char* get_name ( ) const
virtual

return the kernel's name

Returns
name GaussianARDSparseKernel

Reimplemented from CGaussianARDKernel.

Definition at line 66 of file GaussianARDSparseKernel.h.

CKernelNormalizer * get_normalizer ( )
virtualinherited

obtain the current kernel normalizer

Returns
the kernel normalizer

Definition at line 160 of file Kernel.cpp.

int32_t get_num_subkernels ( )
virtualinherited

get number of subkernels

Returns
number of subkernels

Reimplemented in CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCombinedKernel, and CProductKernel.

Definition at line 839 of file Kernel.cpp.

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 517 of file kernel/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 526 of file kernel/Kernel.h.

EOptimizationType get_optimization_type ( )
inherited

get optimization type

Returns
optimization type

Definition at line 742 of file kernel/Kernel.h.

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

return derivative with respect to specified parameter

Parameters
paramthe parameter
indexthe index of the element if parameter is a vector or matrix if the parameter is a matrix, index is the linearized index of the matrix (column-major)
Returns
gradient with respect to parameter

Reimplemented from CGaussianARDKernel.

Definition at line 86 of file GaussianARDSparseKernel.cpp.

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

return diagonal part of derivative with respect to specified parameter

Parameters
paramthe parameter
indexthe index of the element if parameter is a vector
Returns
diagonal part of gradient with respect to parameter

Reimplemented from CGaussianARDKernel.

Definition at line 76 of file GaussianARDSparseKernel.cpp.

float64_t get_parameter_gradient_helper ( const TParameter param,
index_t  index,
int32_t  idx_a,
int32_t  idx_b,
SGVector< float64_t avec,
SGVector< float64_t bvec 
)
protectedvirtualinherited

helper function to compute derivative with respect to specified parameter

Parameters
paramthe parameter
indexthe index of the element if parameter is a vector or matrix if the parameter is a matrix, index is the linearized index of the matrix (column-major)
idx_athe row index of the gradient matrix
idx_bthe column index of the gradient matrix
avecfeature vector corresponding to idx_a
bvecfeature vector corresponding to idx_b
Returns
gradient at row idx_a and column idx_b with respect to parameter

Definition at line 249 of file GaussianARDKernel.cpp.

CFeatures* get_rhs ( )
inherited

get right-hand side of features used in kernel

Returns
features of right-hand side

Definition at line 511 of file kernel/Kernel.h.

const float64_t * get_subkernel_weights ( int32_t &  num_weights)
virtualinherited

get subkernel weights

Parameters
num_weightsnumber of weights will be stored here
Returns
subkernel weights

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.

Definition at line 850 of file Kernel.cpp.

SGVector< float64_t > get_subkernel_weights ( )
virtualinherited

get subkernel weights (swig compatible)

Returns
subkernel weights

Reimplemented in CCombinedKernel.

Definition at line 856 of file Kernel.cpp.

SGMatrix< float64_t > get_weighted_vector ( SGVector< float64_t vec)
protectedinherited

convert the m_log_weights in vector format to the matrix format in standard domain

Parameters
vecweights in log domain in vector layout
Returns
weights in standard domain in matrix layout

Definition at line 212 of file ExponentialARDKernel.cpp.

SGMatrix< float64_t > get_weights ( )
virtualinherited

return current feature/dimension weights in matrix form Note that a vector weights is considered as a row vector (one-by-p matrix) where p is the number of features Note that a scalar weights is considered as a one-by-one matrix

Returns
weights in matrix form

Definition at line 119 of file ExponentialARDKernel.cpp.

bool has ( const std::string &  name) const
inherited

Checks if object has a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name

Definition at line 299 of file SGObject.h.

bool has ( const Tag< T > &  tag) const
inherited

Checks if object has a class parameter identified by a Tag.

Parameters
tagtag of the parameter containing name and type information
Returns
true if the parameter exists with the input tag

Definition at line 310 of file SGObject.h.

bool has ( const std::string &  name) const
inherited

Checks if a type exists for a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name and type

Definition at line 321 of file SGObject.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 535 of file kernel/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 724 of file kernel/Kernel.h.

bool init ( CFeatures l,
CFeatures r 
)
virtualinherited

initialize kernel

Parameters
lfeatures of left-hand side
rfeatures of right-hand side
Returns
if initializing was successful

Reimplemented from CExponentialARDKernel.

Definition at line 73 of file GaussianARDKernel.cpp.

bool init_normalizer ( )
virtualinherited

initialize the current kernel normalizer

Returns
if init was successful

Definition at line 166 of file Kernel.cpp.

bool init_optimization ( int32_t  count,
int32_t *  IDX,
float64_t weights 
)
virtualinherited

initialize optimization

Parameters
countcount
IDXindex
weightsweights
Returns
if initializing was successful

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommWordStringKernel, CCommUlongStringKernel, CLinearKernel, and CLinearStringKernel.

Definition at line 803 of file Kernel.cpp.

bool init_optimization_svm ( CSVM svm)
inherited

initialize optimization

Parameters
svmsvm model
Returns
if initializing was successful

Definition at line 886 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 329 of file SGObject.cpp.

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 207 of file kernel/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 690 of file kernel/Kernel.h.

void kernel_cache_cleanup ( )
inherited

cleanup kernel cache

Definition at line 542 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 179 of file Kernel.cpp.

void kernel_cache_reset_lru ( )
inherited

kernel cache reset lru

Definition at line 529 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 470 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 699 of file kernel/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 675 of file kernel/Kernel.h.

void lazy_update_weights ( )
protectedinherited

convert the weights in log domain to standard domain when get_weights() is called

Definition at line 85 of file ExponentialARDKernel.cpp.

void list_kernel ( )
inherited

list kernel

Definition at line 683 of file Kernel.cpp.

void load ( CFile loader)
inherited

load the kernel matrix

Parameters
loaderFile object via which to load data

Definition at line 621 of file Kernel.cpp.

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

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

Parameters
filewhere to load from
prefixprefix for members
Returns
TRUE if done, otherwise FALSE

Definition at line 402 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 904 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 occurs.

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

Definition at line 454 of file SGObject.cpp.

CGaussianARDSparseKernel * obtain_from_generic ( CKernel kernel)
static
Parameters
kernelis casted to CGaussianARDSparseKernel, error if not possible is SG_REF'ed
Returns
casted CGaussianARDSparseKernel object

Definition at line 64 of file GaussianARDSparseKernel.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 872 of file Kernel.cpp.

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

Definition at line 295 of file SGObject.cpp.

void precompute_squared ( )
protectedvirtualinherited

helper function to compute quadratic terms in (a-b)^2 (== a^2+b^2-2ab)

Definition at line 93 of file GaussianARDKernel.cpp.

SGVector< float64_t > precompute_squared_helper ( CDotFeatures df)
protectedvirtualinherited

helper function to compute quadratic terms in (a-b)^2 (== a^2+b^2-2ab)

Parameters
bufbuffer to store squared terms (will be allocated)
dfdot feature object based on which k(i,i) is computed

Definition at line 83 of file GaussianARDKernel.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 507 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 341 of file SGObject.cpp.

void register_param ( Tag< T > &  _tag,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 450 of file SGObject.h.

void register_param ( const std::string &  name,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 463 of file SGObject.h.

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 927 of file Kernel.cpp.

void remove_lhs ( )
virtualinherited

remove lhs from kernel

Reimplemented in CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCombinedKernel, CCommUlongStringKernel, and CProductKernel.

Definition at line 654 of file Kernel.cpp.

void remove_lhs_and_rhs ( )
virtualinherited

remove lhs and rhs from kernel

Reimplemented in CCombinedKernel, and CProductKernel.

Definition at line 635 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 668 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 83 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 \(j\in[0,\text{block-size-col}-1]\)

Reimplemented in CCustomKernel.

Definition at line 1211 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 \(i,j\in[0,\text{block-size}-1]\)

Reimplemented in CCustomKernel.

Definition at line 1152 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 \(i,j\in[0,\text{block-size}-1]\)

Reimplemented in CCustomKernel.

Definition at line 1098 of file Kernel.cpp.

void save ( CFile writer)
inherited

save kernel matrix

Parameters
writerFile object via which to save data

Definition at line 627 of file Kernel.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "" 
)
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
Returns
TRUE if done, otherwise FALSE

Definition at line 347 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 919 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 911 of file Kernel.cpp.

void set ( const Tag< T > &  _tag,
const T &  value 
)
inherited

Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 337 of file SGObject.h.

void set ( const std::string &  name,
const T &  value 
)
inherited

Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 363 of file SGObject.h.

void set_cache_size ( int32_t  size)
inherited

set the size of the kernel cache

Parameters
sizeof kernel cache

Definition at line 587 of file kernel/Kernel.h.

void set_combined_kernel_weight ( float64_t  nw)
inherited

set combined kernel weight

Parameters
nwnew combined kernel weight

Definition at line 809 of file kernel/Kernel.h.

void set_generic ( )
inherited

Definition at line 74 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 79 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 84 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 89 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 94 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 99 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 104 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 109 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 114 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 119 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 124 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 129 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 134 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 139 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 144 of file SGObject.cpp.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 261 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 274 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 316 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 900 of file kernel/Kernel.h.

void set_matrix_weights ( SGMatrix< float64_t weights)
virtualinherited

setter for feature/dimension weights (matrix kernel)

Parameters
weightsa lower triangular matrix weight with positive diagonal elements

Definition at line 154 of file ExponentialARDKernel.cpp.

bool set_normalizer ( CKernelNormalizer normalizer)
virtualinherited

set the current kernel normalizer

Returns
if successful

Reimplemented in CWeightedDegreeStringKernel.

Definition at line 148 of file Kernel.cpp.

virtual void set_optimization_type ( EOptimizationType  t)
virtualinherited

set optimization type

Parameters
toptimization type to set

Reimplemented in CCombinedKernel.

Definition at line 748 of file kernel/Kernel.h.

void set_property ( EKernelProperty  p)
protectedinherited

set property

Parameters
pkernel property to set

Definition at line 882 of file kernel/Kernel.h.

void set_scalar_weights ( float64_t  weight)
virtualinherited

setter for feature/dimension weight (scalar kernel)

Parameters
weightpositive scalar weight

Definition at line 125 of file ExponentialARDKernel.cpp.

void set_subkernel_weights ( SGVector< float64_t weights)
virtualinherited

set subkernel weights

Parameters
weightsnew subkernel weights

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.

Definition at line 863 of file Kernel.cpp.

void set_time ( int32_t  t)
inherited

set the lru time

Parameters
tthe time to use

Definition at line 665 of file kernel/Kernel.h.

void set_vector_weights ( SGVector< float64_t weights)
virtualinherited

setter for feature/dimension weights (vector kernel)

Parameters
weightspositive vector weight

Definition at line 136 of file ExponentialARDKernel.cpp.

void set_weights ( SGMatrix< float64_t weights)
protectedvirtualinherited

a general setter for feature/dimension weights (matrix kernel)

Parameters
weightsthe weights can be scalar/vector/lower triangular matrix

Definition at line 68 of file ExponentialARDKernel.cpp.

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

Reimplemented in CCustomKernel.

Definition at line 1053 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 \(i,j\in[0,\text{block-size}-1]\)

Reimplemented in CCustomKernel.

Definition at line 1002 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 336 of file SGObject.cpp.

void unset_property ( EKernelProperty  p)
protectedinherited

unset property

Parameters
pkernel property to unset

Definition at line 891 of file kernel/Kernel.h.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 281 of file SGObject.cpp.

Member Data Documentation

int32_t cache_size
protectedinherited

cache_size in MB

Definition at line 1048 of file kernel/Kernel.h.

float64_t combined_kernel_weight
protectedinherited

combined kernel weight

Definition at line 1073 of file kernel/Kernel.h.

SGIO* io
inherited

io

Definition at line 558 of file SGObject.h.

KERNEL_CACHE kernel_cache
protectedinherited

kernel cache

Definition at line 1052 of file kernel/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 1057 of file kernel/Kernel.h.

CFeatures* lhs
protectedinherited

feature vectors to occur on left hand side

Definition at line 1060 of file kernel/Kernel.h.

bool lhs_equals_rhs
protectedinherited

lhs

Definition at line 1065 of file kernel/Kernel.h.

EARDKernelType m_ARD_type
protectedinherited

type of ARD kernel

Definition at line 118 of file ExponentialARDKernel.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 573 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 576 of file SGObject.h.

SGVector<float64_t> m_log_weights
protectedinherited

feature weights in log domain in vector layout

Definition at line 109 of file ExponentialARDKernel.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 570 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 567 of file SGObject.h.

SGVector<float64_t> m_sq_lhs
protectedinherited

squared left-hand side

Definition at line 165 of file GaussianARDKernel.h.

SGVector<float64_t> m_sq_rhs
protectedinherited

squared right-hand side

Definition at line 167 of file GaussianARDKernel.h.

index_t m_weights_cols
protectedinherited

the number of columns of feature weights for vector layout

Definition at line 115 of file ExponentialARDKernel.h.

SGMatrix<float64_t> m_weights_raw
protectedinherited

feature weights in standard domain in the matrix layout, which is only used in get_weights()

Definition at line 106 of file ExponentialARDKernel.h.

index_t m_weights_rows
protectedinherited

the number of rows of feature weights for vector layout

Definition at line 112 of file ExponentialARDKernel.h.

CKernelNormalizer* normalizer
protectedinherited

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

Definition at line 1087 of file kernel/Kernel.h.

int32_t num_lhs
protectedinherited

number of feature vectors on left hand side

Definition at line 1068 of file kernel/Kernel.h.

int32_t num_rhs
protectedinherited

number of feature vectors on right hand side

Definition at line 1070 of file kernel/Kernel.h.

EOptimizationType opt_type
protectedinherited

optimization type (currently FASTBUTMEMHUNGRY and SLOWBUTMEMEFFICIENT)

Definition at line 1080 of file kernel/Kernel.h.

bool optimization_initialized
protectedinherited

if optimization is initialized

Definition at line 1076 of file kernel/Kernel.h.

Parallel* parallel
inherited

parallel

Definition at line 561 of file SGObject.h.

uint64_t properties
protectedinherited

kernel properties

Definition at line 1083 of file kernel/Kernel.h.

CFeatures* rhs
protectedinherited

feature vectors to occur on right hand side

Definition at line 1062 of file kernel/Kernel.h.

Version* version
inherited

version

Definition at line 564 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation