SHOGUN  4.1.0
CGaussianShiftKernel Class Reference

Detailed Description

An experimental kernel inspired by the WeightedDegreePositionStringKernel and the Gaussian kernel.

It is computed as

$k({\bf x},{\bf x'})= \exp(-\frac{||{\bf x}-{\bf x'}||^2}{\tau}) + \sum_{s=1}^{S_{\mathrm{max}}/S_{\mathrm{step}}} \frac{1}{2s} \exp(-\frac{||{\bf x}_{[1:|{\bf x}|-sS_{\mathrm{step}}]}-{\bf x'}_{[sS_{\mathrm{step}}:|{\bf x}|]}||^2}{\tau}) + \sum_{s=1}^{S_{max}/S_{step}} \frac{1}{2s} \exp(-\frac{||{\bf x}_{[sS_{\mathrm{step}}:|{\bf x}|]}-{\bf x'}_{[1:|{\bf x}|-sS_{\mathrm{step}}]}||^2}{\tau}) +$

where $$\tau$$ is the kernel width. The idea is to shift the dimensions of the input vectors against eachother. $$S_{\mathrm{step}}$$ is the step size (parameter shift_step) of the shifts and $$S_{\mathrm{max}}$$ (parameter max_shift) is the maximal shift.

Definition at line 40 of file GaussianShiftKernel.h.

Inheritance diagram for CGaussianShiftKernel:
[legend]

Public Member Functions

CGaussianShiftKernel ()

CGaussianShiftKernel (int32_t size, float64_t width, int32_t max_shift, int32_t shift_step)

CGaussianShiftKernel (CDenseFeatures< float64_t > *l, CDenseFeatures< float64_t > *r, float64_t width, int32_t max_shift, int32_t shift_step, int32_t size=10)

virtual bool init (CFeatures *l, CFeatures *r)

virtual ~CGaussianShiftKernel ()

virtual EKernelType get_kernel_type ()

virtual const char * get_name () const

virtual CSGObjectshallow_copy () const

virtual void cleanup ()

virtual void set_width (float64_t w)

virtual float64_t get_width () const

void set_compact_enabled (bool compact)

bool get_compact_enabled ()

virtual SGMatrix< float64_tget_parameter_gradient (const TParameter *param, index_t index=-1)

virtual EFeatureClass get_feature_class ()

virtual EFeatureType get_feature_type ()

float64_t kernel (int32_t idx_a, int32_t idx_b)

SGMatrix< float64_tget_kernel_matrix ()

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

SGVector< float64_tget_kernel_diagonal (SGVector< float64_t > preallocated=SGVector< float64_t >())

virtual SGVector< float64_tget_kernel_col (int32_t j)

virtual SGVector< float64_tget_kernel_row (int32_t i)

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

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

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

virtual SGVector< float64_trow_wise_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true)

virtual SGMatrix< float64_trow_wise_sum_squared_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true)

virtual SGVector< float64_trow_col_wise_sum_block (index_t block_begin_row, index_t block_begin_col, index_t block_size_row, index_t block_size_col, bool no_diag=false)

virtual bool set_normalizer (CKernelNormalizer *normalizer)

virtual CKernelNormalizerget_normalizer ()

virtual bool init_normalizer ()

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 SGVector< float64_tget_parameter_gradient_diagonal (const TParameter *param, index_t index=-1)

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="", int32_t param_version=Version::get_version_parameter())

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

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

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

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

void set_global_io (SGIO *io)

SGIOget_global_io ()

void set_global_parallel (Parallel *parallel)

Parallelget_global_parallel ()

void set_global_version (Version *version)

Versionget_global_version ()

SGStringList< char > get_modelsel_names ()

void print_modsel_params ()

char * get_modsel_param_descr (const char *param_name)

index_t get_modsel_param_index (const char *param_name)

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

virtual void update_parameter_hash ()

virtual bool parameter_hash_changed ()

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

virtual CSGObjectclone ()

Static Public Member Functions

static CGaussianKernelobtain_from_generic (CKernel *kernel)

static CKernelobtain_from_generic (CSGObject *kernel)

Public Attributes

SGIOio

Parallelparallel

Versionversion

Parameterm_parameters

Parameterm_model_selection_parameters

ParameterMapm_parameter_map

uint32_t m_hash

Protected Member Functions

virtual float64_t compute (int32_t idx_a, int32_t idx_b)

virtual void load_serializable_post () throw (ShogunException)

virtual float64_t distance (int32_t idx_a, int32_t idx_b)

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 save_serializable_pre () throw (ShogunException)

virtual void save_serializable_post () throw (ShogunException)

virtual void register_params ()

virtual TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)

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

virtual void load_serializable_pre () throw (ShogunException)

Static Protected Member Functions

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

Protected Attributes

int32_t max_shift

int32_t shift_step

float64_t width

float64_tsq_lhs

float64_tsq_rhs

bool m_compact

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

 CGaussianShiftKernel ( )

default constructor

Definition at line 18 of file GaussianShiftKernel.cpp.

 CGaussianShiftKernel ( int32_t size, float64_t width, int32_t max_shift, int32_t shift_step )

constructor

Parameters
 size cache size width width max_shift maximum shift shift_step shift step

Definition at line 24 of file GaussianShiftKernel.cpp.

 CGaussianShiftKernel ( CDenseFeatures< float64_t > * l, CDenseFeatures< float64_t > * r, float64_t width, int32_t max_shift, int32_t shift_step, int32_t size = 10 )

constructor

Parameters
 l features of left-hand side r features of right-hand side width width max_shift maximum shift shift_step shift step size cache size

Definition at line 31 of file GaussianShiftKernel.cpp.

 ~CGaussianShiftKernel ( )
virtual

Definition at line 40 of file GaussianShiftKernel.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_idx index weight weight

Definition at line 841 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
 dict dictionary of parameters to be built.

Definition at line 1244 of file SGObject.cpp.

 void cache_kernel_row ( int32_t x )
inherited

cache kernel row

Parameters
 x x

Definition at line 291 of file Kernel.cpp.

 void cache_multiple_kernel_rows ( int32_t * key, int32_t varnum )
inherited

cache multiple kernel rows

Parameters
 key key varnum

Definition at line 365 of file Kernel.cpp.

 void cache_reset ( )
inherited

cache reset

Definition at line 602 of file Kernel.h.

 void cleanup ( )
virtualinherited

clean up kernel

Reimplemented from CKernel.

Definition at line 74 of file GaussianKernel.cpp.

 void clear_normal ( )
virtualinherited

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

Definition at line 846 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

Definition at line 1361 of file SGObject.cpp.

 float64_t compute ( int32_t idx_a, int32_t idx_b )
protectedvirtual

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

Parameters
 idx_a index a idx_b index b
Returns
computed kernel function at indices a,b

Reimplemented from CGaussianKernel.

Definition at line 44 of file GaussianShiftKernel.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 )
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 834 of file Kernel.cpp.

 void compute_by_subkernel ( int32_t vector_idx, float64_t * subkernel_contrib )
virtualinherited

compute by subkernel

Parameters
 vector_idx index subkernel_contrib subkernel contribution

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.

Definition at line 856 of file Kernel.cpp.

 float64_t compute_optimized ( int32_t vector_idx )
virtualinherited

compute optimized

Parameters
 vector_idx index to compute
Returns
optimized value at given index

Definition at line 828 of file Kernel.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
 offs offset n number of columns symmetric whether matrix is symmetric

Definition at line 919 of file Kernel.h.

 CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 200 of file SGObject.cpp.

 bool delete_optimization ( )
virtualinherited

delete optimization

Returns
if deleting was successful

Definition at line 822 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_a index a idx_b index b
Returns
computed the distance

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

$distance({\bf x},{\bf y})= \frac{||{\bf x}-{\bf y}||^2}{\tau}$

Definition at line 183 of file GaussianKernel.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
 other object to compare with accuracy accuracy to use for comparison (optional) tolerant allows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 1265 of file SGObject.cpp.

 int32_t get_activenum_cache ( )
inherited

get activenum cache

Returns
activecnum cache

Definition at line 614 of file Kernel.h.

 int32_t get_cache_size ( )
inherited

return the size of the kernel cache

Returns
size of kernel cache

Definition at line 598 of file Kernel.h.

 float64_t get_combined_kernel_weight ( )
inherited

get combined kernel weight

Returns
combined kernel weight

Definition at line 802 of file Kernel.h.

 bool get_compact_enabled ( )
inherited

return value of the compact option

Returns
whether the compact option is enabled

Definition at line 127 of file GaussianKernel.h.

 virtual EFeatureClass get_feature_class ( )
virtualinherited

return feature class the kernel can deal with

dot kernel returns unknown since features can be based on anything

Returns
feature class ANY

Implements CKernel.

Reimplemented in CLinearARDKernel, CTensorProductPairKernel, CChi2Kernel, CAUCKernel, CANOVAKernel, and CWeightedDegreeRBFKernel.

Definition at line 88 of file DotKernel.h.

 virtual EFeatureType get_feature_type ( )
virtualinherited

return feature type the kernel can deal with

dot kernel returns unknown since features can be based on anything

Returns
ANY feature type

Implements CKernel.

Reimplemented in CLinearARDKernel, CTensorProductPairKernel, CChi2Kernel, CAUCKernel, CWeightedDegreeRBFKernel, and CANOVAKernel.

Definition at line 96 of file DotKernel.h.

 SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 237 of file SGObject.cpp.

 Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 279 of file SGObject.cpp.

 Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 292 of file SGObject.cpp.

 bool get_is_initialized ( )
inherited

check if optimization is initialized

Returns
if optimization is initialized

Definition at line 753 of file Kernel.h.

 virtual SGVector get_kernel_col ( int32_t j )
virtualinherited

get column j

Returns
the jth column of the kernel matrix

Definition at line 262 of file Kernel.h.

 SGVector get_kernel_diagonal ( SGVector< float64_t > preallocated = SGVector() )
inherited
Returns
Vector with diagonal elements of the kernel matrix. Note that left- and right-handside features must be set and of equal size
Parameters
 preallocated vector with space for results

Definition at line 230 of file Kernel.h.

 template SGMatrix< float32_t > get_kernel_matrix< float32_t > ( )
inherited

get kernel matrix

Returns
computed kernel matrix (needs to be cleaned up)

Definition at line 219 of file Kernel.h.

 SGMatrix< T > get_kernel_matrix ( )
inherited

get kernel matrix (templated)

Returns
the kernel matrix

Definition at line 1331 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

Definition at line 1280 of file Kernel.cpp.

 virtual SGVector get_kernel_row ( int32_t i )
virtualinherited

get row i

Returns
the ith row of the kernel matrix

Definition at line 279 of file Kernel.h.

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

get kernel row

Parameters
 docnum docnum active2dnum active2dnum buffer buffer full_line full line

Definition at line 227 of file Kernel.cpp.

 virtual EKernelType get_kernel_type ( )
virtual

return what type of kernel we are

Returns
kernel type GAUSSIANSHIFT

Reimplemented from CGaussianKernel.

Definition at line 88 of file GaussianShiftKernel.h.

 CFeatures* get_lhs ( )
inherited

get left-hand side of features used in kernel

Returns
features of left-hand side

Definition at line 504 of file Kernel.h.

 bool get_lhs_equals_rhs ( )
inherited

test whether features on lhs and rhs are the same

Returns
true if features are the same

Definition at line 543 of file Kernel.h.

 int32_t get_max_elems_cache ( )
inherited

get maximum elements in cache

Returns
maximum elements in cache

Definition at line 608 of file Kernel.h.

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

Definition at line 1136 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 1160 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 1173 of file SGObject.cpp.

 virtual const char* get_name ( ) const
virtual

return the kernel's name

Returns
name GaussianShift

Reimplemented from CGaussianKernel.

Definition at line 94 of file GaussianShiftKernel.h.

 CKernelNormalizer * get_normalizer ( )
virtualinherited

obtain the current kernel normalizer

Returns
the kernel normalizer

Definition at line 151 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 851 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 516 of file Kernel.h.

 virtual int32_t get_num_vec_rhs ( )
virtualinherited

get number of vectors of rhs features

Returns
number of vectors of right-hand side

Reimplemented in CCustomKernel.

Definition at line 525 of file Kernel.h.

 EOptimizationType get_optimization_type ( )
inherited

get optimization type

Returns
optimization type

Definition at line 741 of file Kernel.h.

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

return derivative with respect to specified parameter

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

Reimplemented from CKernel.

Definition at line 148 of file GaussianKernel.cpp.

 virtual SGVector get_parameter_gradient_diagonal ( const TParameter * param, index_t index = -1 )
virtualinherited

return diagonal part of derivative with respect to specified parameter

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

Definition at line 864 of file Kernel.h.

 CFeatures* get_rhs ( )
inherited

get right-hand side of features used in kernel

Returns
features of right-hand side

Definition at line 510 of file Kernel.h.

 const float64_t * get_subkernel_weights ( int32_t & num_weights )
virtualinherited

get subkernel weights

Parameters
 num_weights number of weights will be stored here
Returns
subkernel weights

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.

Definition at line 862 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 868 of file Kernel.cpp.

 virtual float64_t get_width ( ) const
virtualinherited

return the kernel's width

Returns
kernel width

Definition at line 115 of file GaussianKernel.h.

 virtual bool has_features ( )
virtualinherited

test whether features have been assigned to lhs and rhs

Returns
true if features are assigned

Reimplemented in CCustomKernel, CCombinedKernel, and CProductKernel.

Definition at line 534 of file Kernel.h.

 bool has_property ( EKernelProperty p )
inherited

check if kernel has given property

Parameters
 p kernel property
Returns
if kernel has given property

Definition at line 723 of file Kernel.h.

 virtual 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 CGaussianKernel.

Definition at line 77 of file GaussianShiftKernel.h.

 bool init_normalizer ( )
virtualinherited

initialize the current kernel normalizer

Returns
if init was successful

Definition at line 157 of file Kernel.cpp.

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

initialize optimization

Parameters
 count count IDX index weights weights
Returns
if initializing was successful

Definition at line 815 of file Kernel.cpp.

 bool init_optimization_svm ( CSVM * svm )
inherited

initialize optimization

Parameters
 svm svm model
Returns
if initializing was successful

Definition at line 898 of file Kernel.cpp.

 bool is_generic ( EPrimitiveType * generic ) const
virtualinherited

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

Parameters
 generic set to the type of the generic if returning TRUE
Returns
TRUE if a class template.

Definition at line 298 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_a index of feature vector a idx_b index of feature vector b
Returns
computed kernel function

Definition at line 206 of file Kernel.h.

 int32_t kernel_cache_check ( int32_t cacheidx )
inherited

check if row at given index is cached

Parameters
 cacheidx index in cache
Returns
if row at given index is cached

Definition at line 689 of file Kernel.h.

 void kernel_cache_cleanup ( )
inherited

cleanup kernel cache

Definition at line 556 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 170 of file Kernel.cpp.

 void kernel_cache_reset_lru ( )
inherited

kernel cache reset lru

Definition at line 543 of file Kernel.cpp.

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

kernel cache shrink

Parameters
 totdoc totdoc num_shrink number of shrink after after

Definition at line 484 of file Kernel.cpp.

 int32_t kernel_cache_space_available ( )
inherited

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

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

Definition at line 698 of file Kernel.h.

 int32_t kernel_cache_touch ( int32_t cacheidx )
inherited

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

Parameters
 cacheidx index in cache
Returns
if updating was successful

Definition at line 674 of file Kernel.h.

 void list_kernel ( )
inherited

list kernel

Definition at line 697 of file Kernel.cpp.

inherited

Parameters

Definition at line 635 of file Kernel.cpp.

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

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

Parameters
 file_version parameter version of the file current_version version from which mapping begins (you want to use Version::get_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 705 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 546 of file SGObject.cpp.

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

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

Parameters
 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

Definition at line 375 of file SGObject.cpp.

 void load_serializable_post ( ) throw ( ShogunException )
protectedvirtualinherited

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

Exceptions
 ShogunException Will be thrown if an error occurres.

Reimplemented from CKernel.

Definition at line 129 of file GaussianKernel.cpp.

 void load_serializable_pre ( ) throw ( ShogunException )
protectedvirtualinherited

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

Exceptions
 ShogunException will be thrown if an error occurs.

Definition at line 1058 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 743 of file SGObject.cpp.

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

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

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

Parameters
 param_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 950 of file SGObject.cpp.

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

Definition at line 46 of file GaussianKernel.cpp.

 CKernel * obtain_from_generic ( CSGObject * kernel )
staticinherited

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

Parameters
 kernel Object to cast to CKernel, is not SG_REFed
Returns
object casted to CKernel, NULL if not possible

Definition at line 884 of file Kernel.cpp.

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

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

Parameters
 param_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 890 of file SGObject.cpp.

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

Definition at line 264 of file SGObject.cpp.

 void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1112 of file SGObject.cpp.

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

prints registered parameters out

Parameters
 prefix prefix for members

Definition at line 310 of file SGObject.cpp.

 void register_params ( )
protectedvirtualinherited

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

Definition at line 939 of file Kernel.cpp.

 void remove_lhs ( )
virtualinherited

remove lhs from kernel

Definition at line 668 of file Kernel.cpp.

 void remove_lhs_and_rhs ( )
virtualinherited

remove lhs and rhs from kernel

Reimplemented in CCombinedKernel, and CProductKernel.

Definition at line 649 of file Kernel.cpp.

 void remove_rhs ( )
virtualinherited

takes all necessary steps if the rhs is removed from kernel

remove rhs from kernel

Reimplemented in CCombinedKernel, CCommUlongStringKernel, and CProductKernel.

Definition at line 682 of file Kernel.cpp.

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

resize kernel cache

Parameters
 size new size regression_hack hack for regression

Definition at line 85 of file Kernel.cpp.

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

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

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

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

Parameters
 no_diag if true (default is false), the diagonal elements are excluded from the row/col-wise sum, provided that block_size_row and block_size_col are same (i.e. the block is square). Otherwise, these are always added
Returns
a vector whose first block_size_row entries contain row-wise sum of kernel values computed as

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

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

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

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

Definition at line 1226 of file Kernel.cpp.

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

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

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

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

Parameters
 no_diag if true (default), the diagonal elements are excluded from the row/col-wise sum
Returns
a matrix whose first column contains the row-wise sum of kernel values computed as

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

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

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

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

Definition at line 1167 of file Kernel.cpp.

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

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

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

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

Parameters
 no_diag if true (default), the diagonal elements are excluded from the row/col-wise sum
Returns
vector containing row-wise sum computed as

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

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

Definition at line 1113 of file Kernel.cpp.

 void save ( CFile * writer )
inherited

save kernel matrix

Parameters
 writer File object via which to save data

Definition at line 641 of file Kernel.cpp.

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

Save this object to file.

Parameters
 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

Definition at line 316 of file SGObject.cpp.

 void save_serializable_post ( ) throw ( ShogunException )
protectedvirtualinherited

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

Exceptions
 ShogunException Will be thrown if an error occurres.

Reimplemented from CSGObject.

Definition at line 931 of file Kernel.cpp.

 void save_serializable_pre ( ) throw ( ShogunException )
protectedvirtualinherited

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

Exceptions
 ShogunException Will be thrown if an error occurres.

Reimplemented from CSGObject.

Definition at line 923 of file Kernel.cpp.

 void set_cache_size ( int32_t size )
inherited

set the size of the kernel cache

Parameters
 size of kernel cache

Definition at line 586 of file Kernel.h.

 void set_combined_kernel_weight ( float64_t nw )
inherited

set combined kernel weight

Parameters
 nw new combined kernel weight

Definition at line 808 of file Kernel.h.

 void set_compact_enabled ( bool compact )
inherited

set the compact option

Parameters
 compact value of the compact option

Definition at line 121 of file GaussianKernel.h.

 void set_generic ( )
inherited

Definition at line 42 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 47 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 52 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 57 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 62 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 67 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 72 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 77 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 82 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 87 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 92 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 97 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 102 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 107 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 112 of file SGObject.cpp.

 void set_generic ( )
inherited

set generic type to T

 void set_global_io ( SGIO * io )
inherited

set the io object

Parameters
 io io object to use

Definition at line 230 of file SGObject.cpp.

 void set_global_parallel ( Parallel * parallel )
inherited

set the parallel object

Parameters
 parallel parallel object to use

Definition at line 243 of file SGObject.cpp.

 void set_global_version ( Version * version )
inherited

set the version object

Parameters
 version version object to use

Definition at line 285 of file SGObject.cpp.

 void set_is_initialized ( bool p_init )
protectedinherited

set is initialized

Parameters
 p_init if optimization shall be set to initialized

Definition at line 899 of file Kernel.h.

 bool set_normalizer ( CKernelNormalizer * normalizer )
virtualinherited

set the current kernel normalizer

Returns
if successful

Reimplemented in CWeightedDegreeStringKernel.

Definition at line 139 of file Kernel.cpp.

 virtual void set_optimization_type ( EOptimizationType t )
virtualinherited

set optimization type

Parameters
 t optimization type to set

Reimplemented in CCombinedKernel.

Definition at line 747 of file Kernel.h.

 void set_property ( EKernelProperty p )
protectedinherited

set property

Parameters
 p kernel property to set

Definition at line 881 of file Kernel.h.

 void set_subkernel_weights ( SGVector< float64_t > weights )
virtualinherited

set subkernel weights

Parameters
 weights new subkernel weights

Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.

Definition at line 875 of file Kernel.cpp.

 void set_time ( int32_t t )
inherited

set the lru time

Parameters
 t the time to use

Definition at line 664 of file Kernel.h.

 virtual void set_width ( float64_t w )
virtualinherited

set the kernel's width

Parameters
 w kernel width

Definition at line 109 of file GaussianKernel.h.

 CSGObject * shallow_copy ( ) const
virtualinherited

Make a shallow copy of the kernel

Reimplemented from CSGObject.

Definition at line 60 of file GaussianKernel.cpp.

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

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

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

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

Parameters
 no_diag if true (default is false), the diagonal elements are excluded from the sum, provided that block_size_row and block_size_col are same (i.e. the block is square). Otherwise, these are always added
Returns
sum of kernel values within the block computed as

$\sum_{i}\sum_{j}k(i+\text{block-begin-row}, j+\text{block-begin-col})$

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

Definition at line 1067 of file Kernel.cpp.

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

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

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

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

Parameters
 no_diag if true (default), the diagonal elements are excluded from the sum
Returns
sum of kernel values within the block computed as

$\sum_{i}\sum_{j}k(i+\text{block-begin}, j+\text{block-begin})$

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

Definition at line 1014 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 305 of file SGObject.cpp.

 void unset_property ( EKernelProperty p )
protectedinherited

unset property

Parameters
 p kernel property to unset

Definition at line 890 of file Kernel.h.

 void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 250 of file SGObject.cpp.

Member Data Documentation

 int32_t cache_size
protectedinherited

cache_size in MB

Definition at line 1047 of file Kernel.h.

 float64_t combined_kernel_weight
protectedinherited

combined kernel weight

Definition at line 1072 of file Kernel.h.

 SGIO* io
inherited

io

Definition at line 496 of file SGObject.h.

 KERNEL_CACHE kernel_cache
protectedinherited

kernel cache

Definition at line 1051 of file Kernel.h.

 KERNELCACHE_ELEM* kernel_matrix
protectedinherited

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

Definition at line 1056 of file Kernel.h.

 CFeatures* lhs
protectedinherited

feature vectors to occur on left hand side

Definition at line 1059 of file Kernel.h.

 bool lhs_equals_rhs
protectedinherited

lhs

Definition at line 1064 of file Kernel.h.

 bool m_compact
protectedinherited

whether compact output enabled

Definition at line 198 of file GaussianKernel.h.

inherited

parameters wrt which we can compute gradients

Definition at line 511 of file SGObject.h.

 uint32_t m_hash
inherited

Hash of parameter values

Definition at line 517 of file SGObject.h.

 Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 508 of file SGObject.h.

 ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 514 of file SGObject.h.

 Parameter* m_parameters
inherited

parameters

Definition at line 505 of file SGObject.h.

 int32_t max_shift
protected

maximum shift

Definition at line 112 of file GaussianShiftKernel.h.

 CKernelNormalizer* normalizer
protectedinherited

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

Definition at line 1086 of file Kernel.h.

 int32_t num_lhs
protectedinherited

number of feature vectors on left hand side

Definition at line 1067 of file Kernel.h.

 int32_t num_rhs
protectedinherited

number of feature vectors on right hand side

Definition at line 1069 of file Kernel.h.

 EOptimizationType opt_type
protectedinherited

optimization type (currently FASTBUTMEMHUNGRY and SLOWBUTMEMEFFICIENT)

Definition at line 1079 of file Kernel.h.

 bool optimization_initialized
protectedinherited

if optimization is initialized

Definition at line 1075 of file Kernel.h.

 Parallel* parallel
inherited

parallel

Definition at line 499 of file SGObject.h.

 uint64_t properties
protectedinherited

kernel properties

Definition at line 1082 of file Kernel.h.

 CFeatures* rhs
protectedinherited

feature vectors to occur on right hand side

Definition at line 1061 of file Kernel.h.

 int32_t shift_step
protected

shift step

Definition at line 114 of file GaussianShiftKernel.h.

 float64_t* sq_lhs
protectedinherited

squared left-hand side

Definition at line 194 of file GaussianKernel.h.

 float64_t* sq_rhs
protectedinherited

squared right-hand side

Definition at line 196 of file GaussianKernel.h.

 Version* version
inherited

version

Definition at line 502 of file SGObject.h.

 float64_t width
protectedinherited

width

Definition at line 192 of file GaussianKernel.h.

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

SHOGUN Machine Learning Toolbox - Documentation