SHOGUN
4.1.0
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the class Bessel kernel
It is defined as
\[ k(x, y) = \frac{J_{v}( \| x-y \|/\tau)}{ \| x-y \| ^ {-nv} } \]
Where: \(J_{v}\) is the Bessel funcion with order \(v\), \(\tau\) is the kernel width, and \(n\) is the kernel degree.
Definition at line 34 of file BesselKernel.h.
Public Member Functions | |
CBesselKernel () | |
CBesselKernel (int32_t size, float64_t order, float64_t width, int32_t degree, CDistance *dist) | |
CBesselKernel (CFeatures *l, CFeatures *r, float64_t order, float64_t width, int32_t degree, CDistance *dist, int32_t size=10) | |
virtual | ~CBesselKernel () |
virtual bool | init (CFeatures *l, CFeatures *r) |
virtual void | cleanup () |
virtual EKernelType | get_kernel_type () |
virtual EFeatureType | get_feature_type () |
virtual EFeatureClass | get_feature_class () |
virtual const char * | get_name () const |
virtual void | set_order (float64_t v) |
virtual float64_t | get_order () const |
virtual void | set_width (float64_t tau) |
virtual float64_t | get_width () const |
virtual void | set_degree (int32_t n) |
virtual int32_t | get_degree () const |
virtual void | register_params () |
float64_t | kernel (int32_t idx_a, int32_t idx_b) |
SGMatrix< float64_t > | get_kernel_matrix () |
template<class T > | |
SGMatrix< T > | get_kernel_matrix () |
SGVector< float64_t > | get_kernel_diagonal (SGVector< float64_t > preallocated=SGVector< float64_t >()) |
virtual SGVector< float64_t > | get_kernel_col (int32_t j) |
virtual SGVector< float64_t > | get_kernel_row (int32_t i) |
void | get_kernel_row (int32_t docnum, int32_t *active2dnum, float64_t *buffer, bool full_line=false) |
virtual float64_t | sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true) |
virtual float64_t | sum_block (index_t block_begin_row, index_t block_begin_col, index_t block_size_row, index_t block_size_col, bool no_diag=false) |
virtual SGVector< float64_t > | row_wise_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true) |
virtual SGMatrix< float64_t > | row_wise_sum_squared_sum_symmetric_block (index_t block_begin, index_t block_size, bool no_diag=true) |
virtual SGVector< float64_t > | row_col_wise_sum_block (index_t block_begin_row, index_t block_begin_col, index_t block_size_row, index_t block_size_col, bool no_diag=false) |
virtual bool | set_normalizer (CKernelNormalizer *normalizer) |
virtual CKernelNormalizer * | get_normalizer () |
virtual bool | init_normalizer () |
void | load (CFile *loader) |
void | save (CFile *writer) |
CFeatures * | get_lhs () |
CFeatures * | get_rhs () |
virtual int32_t | get_num_vec_lhs () |
virtual int32_t | get_num_vec_rhs () |
virtual bool | has_features () |
bool | get_lhs_equals_rhs () |
virtual void | remove_lhs_and_rhs () |
virtual void | remove_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_t * | get_subkernel_weights (int32_t &num_weights) |
virtual SGVector< float64_t > | get_subkernel_weights () |
virtual void | set_subkernel_weights (SGVector< float64_t > weights) |
virtual SGMatrix< float64_t > | get_parameter_gradient (const TParameter *param, index_t index=-1) |
virtual SGVector< float64_t > | get_parameter_gradient_diagonal (const TParameter *param, index_t index=-1) |
virtual CSGObject * | shallow_copy () const |
virtual CSGObject * | deep_copy () const |
virtual bool | is_generic (EPrimitiveType *generic) const |
template<class T > | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
void | unset_generic () |
virtual void | print_serializable (const char *prefix="") |
virtual bool | save_serializable (CSerializableFile *file, const char *prefix="") |
virtual bool | load_serializable (CSerializableFile *file, const char *prefix="") |
void | set_global_io (SGIO *io) |
SGIO * | get_global_io () |
void | set_global_parallel (Parallel *parallel) |
Parallel * | get_global_parallel () |
void | set_global_version (Version *version) |
Version * | get_global_version () |
SGStringList< char > | get_modelsel_names () |
void | print_modsel_params () |
char * | get_modsel_param_descr (const char *param_name) |
index_t | get_modsel_param_index (const char *param_name) |
void | build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict) |
virtual void | update_parameter_hash () |
virtual bool | parameter_hash_changed () |
virtual bool | equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false) |
virtual CSGObject * | clone () |
Static Public Member Functions | |
static CKernel * | obtain_from_generic (CSGObject *kernel) |
Public Attributes | |
SGIO * | io |
Parallel * | parallel |
Version * | version |
Parameter * | m_parameters |
Parameter * | m_model_selection_parameters |
Parameter * | m_gradient_parameters |
uint32_t | m_hash |
Protected Member Functions | |
float64_t | compute (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 | load_serializable_post () throw (ShogunException) |
virtual void | save_serializable_pre () throw (ShogunException) |
virtual void | save_serializable_post () throw (ShogunException) |
virtual void | load_serializable_pre () throw (ShogunException) |
Static Protected Member Functions | |
template<class T > | |
static void * | get_kernel_matrix_helper (void *p) |
Protected Attributes | |
float64_t | order |
int32_t | degree |
CDistance * | distance |
float64_t | width |
int32_t | cache_size |
cache_size in MB More... | |
KERNEL_CACHE | kernel_cache |
kernel cache More... | |
KERNELCACHE_ELEM * | kernel_matrix |
CFeatures * | lhs |
feature vectors to occur on left hand side More... | |
CFeatures * | rhs |
feature vectors to occur on right hand side More... | |
bool | lhs_equals_rhs |
lhs More... | |
int32_t | num_lhs |
number of feature vectors on left hand side More... | |
int32_t | num_rhs |
number of feature vectors on right hand side More... | |
float64_t | combined_kernel_weight |
bool | optimization_initialized |
EOptimizationType | opt_type |
uint64_t | properties |
CKernelNormalizer * | normalizer |
CBesselKernel | ( | ) |
default constructor
Definition at line 17 of file BesselKernel.cpp.
CBesselKernel | ( | int32_t | size, |
float64_t | order, | ||
float64_t | width, | ||
int32_t | degree, | ||
CDistance * | dist | ||
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constructor
size | cache size |
order | the order of the bessel function |
width | the kernel width |
degree | the kernel degree |
dist | distance to be used |
Definition at line 22 of file BesselKernel.cpp.
CBesselKernel | ( | CFeatures * | l, |
CFeatures * | r, | ||
float64_t | order, | ||
float64_t | width, | ||
int32_t | degree, | ||
CDistance * | dist, | ||
int32_t | size = 10 |
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) |
constructor
l | features of left-hand side |
r | features of right-hand side |
order | of the bessel function |
width | the kernel width |
degree | the degree |
dist | distance to be used |
size | cache size |
Definition at line 31 of file BesselKernel.cpp.
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clean up kernel
Definition at line 41 of file BesselKernel.cpp.
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add vector*factor to 'virtual' normal vector
vector_idx | index |
weight | weight |
Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommUlongStringKernel, CCommWordStringKernel, CLinearKernel, CLinearStringKernel, and CWeightedCommWordStringKernel.
Definition at line 853 of file Kernel.cpp.
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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.
dict | dictionary of parameters to be built. |
Definition at line 597 of file SGObject.cpp.
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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 858 of file Kernel.cpp.
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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.
Definition at line 714 of file SGObject.cpp.
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compute kernel function for features a and b idx_{a,b} denote the index of the feature vectors in the corresponding feature object
abstract base method
x | index a |
y | index b |
Implements CKernel.
Definition at line 65 of file BesselKernel.cpp.
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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 846 of file Kernel.cpp.
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compute by subkernel
vector_idx | index |
subkernel_contrib | subkernel contribution |
Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.
Definition at line 868 of file Kernel.cpp.
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compute optimized
vector_idx | index to compute |
Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommWordStringKernel, CCommUlongStringKernel, CLinearKernel, CLinearStringKernel, and CWeightedCommWordStringKernel.
Definition at line 840 of file Kernel.cpp.
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A deep copy. All the instance variables will also be copied.
Definition at line 198 of file SGObject.cpp.
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delete optimization
Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommWordStringKernel, CCommUlongStringKernel, CLinearKernel, and CLinearStringKernel.
Definition at line 834 of file Kernel.cpp.
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.
other | object to compare with |
accuracy | accuracy to use for comparison (optional) |
tolerant | allows linient check on float equality (within accuracy) |
Definition at line 618 of file SGObject.cpp.
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Reimplemented from CDistanceKernel.
Definition at line 102 of file BesselKernel.h.
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Reimplemented from CDistanceKernel.
Definition at line 94 of file BesselKernel.h.
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helper for computing the kernel matrix in a parallel way
p | thread parameters |
Definition at line 1292 of file Kernel.cpp.
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get kernel row
docnum | docnum |
active2dnum | active2dnum |
buffer | buffer |
full_line | full line |
Definition at line 238 of file Kernel.cpp.
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return what type of kernel we are
Reimplemented from CDistanceKernel.
Definition at line 86 of file BesselKernel.h.
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Definition at line 498 of file SGObject.cpp.
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Returns description of a given parameter string, if it exists. SG_ERROR otherwise
param_name | name of the parameter |
Definition at line 522 of file SGObject.cpp.
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Returns index of model selection parameter with provided index
param_name | name of model selection parameter |
Definition at line 535 of file SGObject.cpp.
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return the kernel's name
Reimplemented from CDistanceKernel.
Definition at line 111 of file BesselKernel.h.
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obtain the current kernel normalizer
Definition at line 162 of file Kernel.cpp.
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get number of subkernels
Reimplemented in CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCombinedKernel, and CProductKernel.
Definition at line 863 of file Kernel.cpp.
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get number of vectors of lhs features
Reimplemented in CCustomKernel.
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get number of vectors of rhs features
Reimplemented in CCustomKernel.
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return derivative with respect to specified parameter
param | the parameter |
index | the index of the element if parameter is a vector |
Reimplemented in CCombinedKernel, CProductKernel, CGaussianKernel, and CPeriodicKernel.
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get subkernel weights
num_weights | number of weights will be stored here |
Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.
Definition at line 874 of file Kernel.cpp.
get subkernel weights (swig compatible)
Reimplemented in CCombinedKernel.
Definition at line 880 of file Kernel.cpp.
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return the kernel's width
Reimplemented from CDistanceKernel.
Definition at line 147 of file BesselKernel.h.
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test whether features have been assigned to lhs and rhs
Reimplemented in CCustomKernel, CCombinedKernel, and CProductKernel.
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initialize kernel
l | features of left-hand side |
r | features of right-hand side |
Reimplemented from CDistanceKernel.
Definition at line 51 of file BesselKernel.cpp.
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initialize the current kernel normalizer
Definition at line 168 of file Kernel.cpp.
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initialize optimization
count | count |
IDX | index |
weights | weights |
Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCommWordStringKernel, CCommUlongStringKernel, CLinearKernel, and CLinearStringKernel.
Definition at line 827 of file Kernel.cpp.
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initialize optimization
svm | svm model |
Definition at line 910 of file Kernel.cpp.
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If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.
generic | set to the type of the generic if returning TRUE |
Definition at line 296 of file SGObject.cpp.
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cleanup kernel cache
Definition at line 567 of file Kernel.cpp.
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initialize kernel cache
size | size to initialize to |
regression_hack | if hack for regression shall be applied |
Definition at line 181 of file Kernel.cpp.
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kernel cache reset lru
Definition at line 554 of file Kernel.cpp.
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kernel cache shrink
totdoc | totdoc |
num_shrink | number of shrink |
after | after |
Definition at line 495 of file Kernel.cpp.
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list kernel
Definition at line 708 of file Kernel.cpp.
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load the kernel matrix
loader | File object via which to load data |
Definition at line 646 of file Kernel.cpp.
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Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!
file | where to load from |
prefix | prefix for members |
Definition at line 369 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented from CSGObject.
Reimplemented in CWeightedDegreePositionStringKernel, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 928 of file Kernel.cpp.
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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.
ShogunException | will be thrown if an error occurs. |
Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 421 of file SGObject.cpp.
Obtains a kernel from a generic SGObject with error checking. Note that if passing NULL, result will be NULL
kernel | Object to cast to CKernel, is not SG_REFed |
Definition at line 896 of file Kernel.cpp.
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Definition at line 262 of file SGObject.cpp.
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prints all parameter registered for model selection and their type
Definition at line 474 of file SGObject.cpp.
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prints registered parameters out
prefix | prefix for members |
Definition at line 308 of file SGObject.cpp.
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register the parameters (serialization support)
Reimplemented from CKernel.
Definition at line 68 of file DistanceKernel.cpp.
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remove lhs from kernel
Reimplemented in CWeightedDegreeStringKernel, CWeightedDegreePositionStringKernel, CCombinedKernel, CCommUlongStringKernel, and CProductKernel.
Definition at line 679 of file Kernel.cpp.
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remove lhs and rhs from kernel
Reimplemented in CCombinedKernel, and CProductKernel.
Definition at line 660 of file Kernel.cpp.
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takes all necessary steps if the rhs is removed from kernel
remove rhs from kernel
Reimplemented in CCombinedKernel, CCommUlongStringKernel, and CProductKernel.
Definition at line 693 of file Kernel.cpp.
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resize kernel cache
size | new size |
regression_hack | hack for regression |
Definition at line 85 of file Kernel.cpp.
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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.
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
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 |
\[ v[i]=\sum_{j}k(i+\text{block-begin-row}, j+\text{block-begin-col}) \]
and rest block_size_col entries col-wise sum of kernel values computed as\[ v[\text{block-size-row}+j]=\sum_{i}k(i+\text{block-begin-row}, j+\text{block-begin-col}) \]
where \(i\in[0,\text{block-size-row}-1]\) and \(j\in[0,\text{block-size-col}-1]\)Definition at line 1238 of file Kernel.cpp.
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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.
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
no_diag | if true (default), the diagonal elements are excluded from the row/col-wise sum |
\[ v_0[i]=\sum_{j}k(i+\text{block-begin}, j+\text{block-begin}) \]
and second column contains the row-wise sum of squared kernel values\[ v_1[i]=\sum_{j}^k^2(i+\text{block-begin}, j+\text{block-begin}) \]
where \(i,j\in[0,\text{block-size}-1]\)Definition at line 1179 of file Kernel.cpp.
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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.
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
no_diag | if true (default), the diagonal elements are excluded from the row/col-wise sum |
\[ v[i]=\sum_{j}k(i+\text{block-begin}, j+\text{block-begin}) \]
where \(i,j\in[0,\text{block-size}-1]\)Definition at line 1125 of file Kernel.cpp.
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save kernel matrix
writer | File object via which to save data |
Definition at line 652 of file Kernel.cpp.
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Save this object to file.
file | where to save the object; will be closed during returning if PREFIX is an empty string. |
prefix | prefix for members |
Definition at line 314 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented from CSGObject.
Definition at line 943 of file Kernel.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented from CSGObject.
Definition at line 935 of file Kernel.cpp.
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Definition at line 41 of file SGObject.cpp.
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Definition at line 46 of file SGObject.cpp.
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Definition at line 51 of file SGObject.cpp.
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Definition at line 56 of file SGObject.cpp.
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Definition at line 61 of file SGObject.cpp.
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Definition at line 66 of file SGObject.cpp.
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Definition at line 71 of file SGObject.cpp.
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Definition at line 76 of file SGObject.cpp.
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Definition at line 81 of file SGObject.cpp.
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Definition at line 86 of file SGObject.cpp.
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Definition at line 91 of file SGObject.cpp.
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Definition at line 96 of file SGObject.cpp.
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Definition at line 101 of file SGObject.cpp.
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Definition at line 106 of file SGObject.cpp.
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Definition at line 111 of file SGObject.cpp.
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set generic type to T
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set the parallel object
parallel | parallel object to use |
Definition at line 241 of file SGObject.cpp.
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set the version object
version | version object to use |
Definition at line 283 of file SGObject.cpp.
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set the current kernel normalizer
Reimplemented in CWeightedDegreeStringKernel.
Definition at line 150 of file Kernel.cpp.
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set subkernel weights
weights | new subkernel weights |
Reimplemented in CCombinedKernel, CWeightedDegreeStringKernel, and CWeightedDegreePositionStringKernel.
Definition at line 887 of file Kernel.cpp.
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set the kernel's width
tau | kernel width |
Reimplemented from CDistanceKernel.
Definition at line 138 of file BesselKernel.h.
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A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
Reimplemented in CGaussianKernel.
Definition at line 192 of file SGObject.cpp.
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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.
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
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 |
\[ \sum_{i}\sum_{j}k(i+\text{block-begin-row}, j+\text{block-begin-col}) \]
where \(i\in[0,\text{block-size-row}-1]\) and \(j\in[0,\text{block-size-col}-1]\)Definition at line 1079 of file Kernel.cpp.
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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.
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
no_diag | if true (default), the diagonal elements are excluded from the sum |
\[ \sum_{i}\sum_{j}k(i+\text{block-begin}, j+\text{block-begin}) \]
where \(i,j\in[0,\text{block-size}-1]\)Definition at line 1026 of file Kernel.cpp.
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unset generic type
this has to be called in classes specializing a template class
Definition at line 303 of file SGObject.cpp.
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Updates the hash of current parameter combination
Definition at line 248 of file SGObject.cpp.
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kernel degree
Definition at line 180 of file BesselKernel.h.
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distance
Definition at line 125 of file DistanceKernel.h.
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io
Definition at line 369 of file SGObject.h.
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parameters wrt which we can compute gradients
Definition at line 384 of file SGObject.h.
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Hash of parameter values
Definition at line 387 of file SGObject.h.
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model selection parameters
Definition at line 381 of file SGObject.h.
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parameters
Definition at line 378 of file SGObject.h.
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order of the Bessel function
Definition at line 178 of file BesselKernel.h.
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parallel
Definition at line 372 of file SGObject.h.
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version
Definition at line 375 of file SGObject.h.
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width
Definition at line 127 of file DistanceKernel.h.