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CSparseFeatures< ST > Class Template Reference

Detailed Description

template<class ST>
class shogun::CSparseFeatures< ST >

Template class SparseFeatures implements sparse matrices.

Features are an array of SGSparseVector. Within each vector feat_index are sorted (increasing).

Sparse feature vectors can be accessed via get_sparse_feature_vector() and should be freed (this operation is a NOP in most cases) via free_sparse_feature_vector().

As this is a template class it can directly be used for different data types like sparse matrices of real valued, integer, byte etc type.

(Partly) subset access is supported for this feature type. Simple use the (inherited) add_subset(), remove_subset() functions. If done, all calls that work with features are translated to the subset. See comments to find out whether it is supported for that method. See also CFeatures class documentation

Definition at line 56 of file SparseFeatures.h.

Inheritance diagram for CSparseFeatures< ST >:
Inheritance graph
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Public Member Functions

 CSparseFeatures (int32_t size=0)
 CSparseFeatures (SGSparseVector< ST > *src, int32_t num_feat, int32_t num_vec, bool copy=false)
 CSparseFeatures (SGSparseMatrix< ST > sparse)
 CSparseFeatures (SGMatrix< ST > dense)
 CSparseFeatures (const CSparseFeatures &orig)
 CSparseFeatures (CFile *loader)
virtual ~CSparseFeatures ()
void free_sparse_feature_matrix ()
void free_sparse_features ()
virtual CFeaturesduplicate () const
ST get_feature (int32_t num, int32_t index)
ST * get_full_feature_vector (int32_t num, int32_t &len)
SGVector< ST > get_full_feature_vector (int32_t num)
virtual int32_t get_nnz_features_for_vector (int32_t num)
SGSparseVector< ST > get_sparse_feature_vector (int32_t num)
ST dense_dot (ST alpha, int32_t num, ST *vec, int32_t dim, ST b)
void add_to_dense_vec (float64_t alpha, int32_t num, float64_t *vec, int32_t dim, bool abs_val=false)
void free_sparse_feature_vector (int32_t num)
SGSparseVector< ST > * get_sparse_feature_matrix (int32_t &num_feat, int32_t &num_vec)
SGSparseMatrix< ST > get_sparse_feature_matrix ()
CSparseFeatures< ST > * get_transposed ()
SGSparseVector< ST > * get_transposed (int32_t &num_feat, int32_t &num_vec)
void set_sparse_feature_matrix (SGSparseMatrix< ST > sm)
SGMatrix< ST > get_full_feature_matrix ()
virtual bool set_full_feature_matrix (SGMatrix< ST > full)
virtual bool apply_preprocessor (bool force_preprocessing=false)
virtual int32_t get_size () const
bool obtain_from_simple (CDenseFeatures< ST > *sf)
virtual int32_t get_num_vectors () const
int32_t get_num_features ()
int32_t set_num_features (int32_t num)
virtual EFeatureClass get_feature_class () const
virtual EFeatureType get_feature_type () const
void free_feature_vector (int32_t num)
int64_t get_num_nonzero_entries ()
float64_tcompute_squared (float64_t *sq)
float64_t compute_squared_norm (CSparseFeatures< float64_t > *lhs, float64_t *sq_lhs, int32_t idx_a, CSparseFeatures< float64_t > *rhs, float64_t *sq_rhs, int32_t idx_b)
void load (CFile *loader)
void save (CFile *writer)
CRegressionLabelsload_svmlight_file (char *fname, bool do_sort_features=true)
void sort_features ()
bool write_svmlight_file (char *fname, CRegressionLabels *label)
virtual int32_t get_dim_feature_space () const
virtual float64_t dot (int32_t vec_idx1, CDotFeatures *df, int32_t vec_idx2)
virtual float64_t dense_dot (int32_t vec_idx1, const float64_t *vec2, int32_t vec2_len)
virtual void * get_feature_iterator (int32_t vector_index)
virtual bool get_next_feature (int32_t &index, float64_t &value, void *iterator)
virtual void free_feature_iterator (void *iterator)
virtual CFeaturescopy_subset (SGVector< index_t > indices)
virtual const char * get_name () const
virtual float64_t dense_dot_sgvec (int32_t vec_idx1, const SGVector< float64_t > vec2)
virtual void dense_dot_range (float64_t *output, int32_t start, int32_t stop, float64_t *alphas, float64_t *vec, int32_t dim, float64_t b)
virtual void dense_dot_range_subset (int32_t *sub_index, int32_t num, float64_t *output, float64_t *alphas, float64_t *vec, int32_t dim, float64_t b)
float64_t get_combined_feature_weight ()
void set_combined_feature_weight (float64_t nw)
SGMatrix< float64_tget_computed_dot_feature_matrix ()
SGVector< float64_tget_computed_dot_feature_vector (int32_t num)
void benchmark_add_to_dense_vector (int32_t repeats=5)
void benchmark_dense_dot_range (int32_t repeats=5)
virtual SGVector< float64_tget_mean ()
virtual SGMatrix< float64_tget_cov ()
virtual int32_t add_preprocessor (CPreprocessor *p)
 set preprocessor
virtual CPreprocessordel_preprocessor (int32_t num)
 del current preprocessor
CPreprocessorget_preprocessor (int32_t num) const
 get current preprocessor
void set_preprocessed (int32_t num)
bool is_preprocessed (int32_t num) const
int32_t get_num_preprocessed () const
 get whether specified preprocessor (or all if num=1) was/were already applied
int32_t get_num_preprocessors () const
void clean_preprocessors ()
int32_t get_cache_size () const
virtual bool reshape (int32_t num_features, int32_t num_vectors)
void list_feature_obj () const
bool check_feature_compatibility (CFeatures *f) const
bool has_property (EFeatureProperty p) const
void set_property (EFeatureProperty p)
void unset_property (EFeatureProperty p)
virtual CFeaturescreate_merged_copy (CFeatures *other)
virtual void add_subset (SGVector< index_t > subset)
virtual void remove_subset ()
virtual void remove_all_subsets ()
virtual CSubsetStackget_subset_stack ()
virtual void subset_changed_post ()
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_copy () const
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=VERSION_PARAMETER)
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=VERSION_PARAMETER)
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
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_parameter_dictionary (CMap< TParameter *, CSGObject * > &dict)

Static Public Member Functions

static ST sparse_dot (ST alpha, SGSparseVectorEntry< ST > *avec, int32_t alen, SGSparseVectorEntry< ST > *bvec, int32_t blen)
static void * dense_dot_range_helper (void *p)
static SGVector< float64_tget_mean (CDotFeatures *lhs, CDotFeatures *rhs)
static SGMatrix< float64_tcompute_cov (CDotFeatures *lhs, CDotFeatures *rhs)

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

virtual SGSparseVectorEntry< ST > * compute_sparse_feature_vector (int32_t num, int32_t &len, SGSparseVectorEntry< ST > *target=NULL)
void display_progress (int32_t start, int32_t stop, int32_t v)
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)
virtual void load_serializable_post () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)
virtual bool update_parameter_hash ()

Protected Attributes

int32_t num_vectors
 total number of vectors
int32_t num_features
 total number of features
SGSparseVector< ST > * sparse_feature_matrix
 array of sparse vectors of size num_vectors
CCache< SGSparseVectorEntry
< ST > > * 
feature_cache
float64_t combined_weight
 feature weighting in combined dot features
CSubsetStackm_subset_stack

Constructor & Destructor Documentation

CSparseFeatures ( int32_t  size = 0)

constructor

Parameters
sizecache size

Definition at line 14 of file SparseFeatures.cpp.

CSparseFeatures ( SGSparseVector< ST > *  src,
int32_t  num_feat,
int32_t  num_vec,
bool  copy = false 
)

convenience constructor that creates sparse features from the ones passed as argument

Parameters
srcdense feature matrix
num_featnumber of features
num_vecnumber of vectors
copytrue to copy feature matrix

Definition at line 21 of file SparseFeatures.cpp.

CSparseFeatures ( SGSparseMatrix< ST >  sparse)

convenience constructor that creates sparse features from sparse features

Parameters
sparsesparse matrix

Definition at line 37 of file SparseFeatures.cpp.

CSparseFeatures ( SGMatrix< ST >  dense)

convenience constructor that creates sparse features from dense features

Parameters
densedense feature matrix

Definition at line 46 of file SparseFeatures.cpp.

CSparseFeatures ( const CSparseFeatures< ST > &  orig)

copy constructor

Definition at line 55 of file SparseFeatures.cpp.

CSparseFeatures ( CFile loader)

constructor loading features from file

Parameters
loaderFile object to load data from

Definition at line 79 of file SparseFeatures.cpp.

~CSparseFeatures ( )
virtual

default destructor

Definition at line 88 of file SparseFeatures.cpp.

Member Function Documentation

int32_t add_preprocessor ( CPreprocessor p)
virtualinherited

set preprocessor

add preprocessor

Parameters
ppreprocessor to set
Returns
something inty

Definition at line 81 of file Features.cpp.

void add_subset ( SGVector< index_t subset)
virtualinherited

adds a subset of indices on top of the current subsets (possibly subset o subset. Calls subset_changed_post() afterwards

Parameters
subsetsubset of indices to add

Reimplemented in CCombinedFeatures.

Definition at line 351 of file Features.cpp.

void add_to_dense_vec ( float64_t  alpha,
int32_t  num,
float64_t vec,
int32_t  dim,
bool  abs_val = false 
)
virtual

add a sparse feature vector onto a dense one dense+=alpha*sparse

possible with subset

Parameters
alphascalar to multiply with
numindex of feature vector
vecdense vector
dimlength of the dense vector
abs_valif true, do dense+=alpha*abs(sparse)

Implements CDotFeatures.

Definition at line 320 of file SparseFeatures.cpp.

bool apply_preprocessor ( bool  force_preprocessing = false)
virtual

apply preprocessor

possible with subset

Parameters
force_preprocessingif preprocssing shall be forced
Returns
if applying was successful

Definition at line 553 of file SparseFeatures.cpp.

void benchmark_add_to_dense_vector ( int32_t  repeats = 5)
inherited

run benchmark for add_to_dense_vec

Definition at line 318 of file DotFeatures.cpp.

void benchmark_dense_dot_range ( int32_t  repeats = 5)
inherited

run benchmark for dense_dot_range

Definition at line 341 of file DotFeatures.cpp.

void build_parameter_dictionary ( CMap< TParameter *, CSGObject * > &  dict)
inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters
dictdictionary of parameters to be built.

Definition at line 1204 of file SGObject.cpp.

bool check_feature_compatibility ( CFeatures f) const
inherited

check feature compatibility

Parameters
ffeatures to check for compatibility
Returns
if features are compatible

Definition at line 326 of file Features.cpp.

void clean_preprocessors ( )
inherited

clears all preprocs

Definition at line 137 of file Features.cpp.

SGMatrix< float64_t > compute_cov ( CDotFeatures lhs,
CDotFeatures rhs 
)
staticinherited

compute the covariance of two CDotFeatures together

Returns
covariance

Definition at line 469 of file DotFeatures.cpp.

SGSparseVectorEntry< ST > * compute_sparse_feature_vector ( int32_t  num,
int32_t &  len,
SGSparseVectorEntry< ST > *  target = NULL 
)
protectedvirtual

compute feature vector for sample num if target is set the vector is written to target len is returned by reference

NOT IMPLEMENTED!

Parameters
numnum
lenlen
targettarget

Definition at line 1073 of file SparseFeatures.cpp.

float64_t * compute_squared ( float64_t sq)

compute a^2 on all feature vectors

possible with subset

Parameters
sqthe square for each vector is stored in here
Returns
the square for each vector

Definition at line 633 of file SparseFeatures.cpp.

float64_t compute_squared_norm ( CSparseFeatures< float64_t > *  lhs,
float64_t sq_lhs,
int32_t  idx_a,
CSparseFeatures< float64_t > *  rhs,
float64_t sq_rhs,
int32_t  idx_b 
)

compute (a-b)^2 (== a^2+b^2-2ab) usually called by kernels'/distances' compute functions works on two feature vectors, although it is a member of a single feature: can either be called by lhs or rhs.

possible wiht subsets on lhs or rhs

Parameters
lhsleft-hand side features
sq_lhssquared values of left-hand side
idx_aindex of left-hand side's vector to compute
rhsright-hand side features
sq_rhssquared values of right-hand side
idx_bindex of right-hand side's vector to compute

Definition at line 652 of file SparseFeatures.cpp.

CFeatures * copy_subset ( SGVector< index_t indices)
virtual

Creates a new CFeatures instance containing copies of the elements which are specified by the provided indices.

Parameters
indicesindices of feature elements to copy
Returns
new CFeatures instance with copies of feature data

Reimplemented from CFeatures.

Definition at line 1050 of file SparseFeatures.cpp.

virtual CFeatures* create_merged_copy ( CFeatures other)
virtualinherited

Takes another feature instance and returns a new instance which is a concatenation of a copy if this instace's data and the given instance's data. Note that the feature types have to be equal.

NOT IMPLEMENTED!

Parameters
otherfeature object to append
Returns
new feature object which contains copy of data of this instance and of given one

Reimplemented in CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, CDenseFeatures< uint16_t >, and CCombinedFeatures.

Definition at line 234 of file Features.h.

virtual CSGObject* deep_copy ( ) const
virtualinherited

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

Definition at line 131 of file SGObject.h.

CPreprocessor * del_preprocessor ( int32_t  num)
virtualinherited

del current preprocessor

delete preprocessor from list caller has to clean up returned preproc

Parameters
numindex of preprocessor in list

Definition at line 143 of file Features.cpp.

ST dense_dot ( ST  alpha,
int32_t  num,
ST *  vec,
int32_t  dim,
ST  b 
)

compute the dot product between dense weights and a sparse feature vector alpha * sparse^T * w + b

possible with subset

Parameters
alphascalar to multiply with
numindex of feature vector
vecdense vector to compute dot product with
dimlength of the dense vector
bbias
Returns
dot product between dense weights and a sparse feature vector

Definition at line 299 of file SparseFeatures.cpp.

float64_t dense_dot ( int32_t  vec_idx1,
const float64_t vec2,
int32_t  vec2_len 
)
virtual

compute dot product between vector1 and a dense vector

possible with subset

Parameters
vec_idx1index of first vector
vec2pointer to real valued vector
vec2_lenlength of real valued vector

Implements CDotFeatures.

Definition at line 984 of file SparseFeatures.cpp.

void dense_dot_range ( float64_t output,
int32_t  start,
int32_t  stop,
float64_t alphas,
float64_t vec,
int32_t  dim,
float64_t  b 
)
virtualinherited

Compute the dot product for a range of vectors. This function makes use of dense_dot alphas[i] * sparse[i]^T * w + b

Parameters
outputresult for the given vector range
startstart vector range from this idx
stopstop vector range at this idx
alphasscalars to multiply with, may be NULL
vecdense vector to compute dot product with
dimlength of the dense vector
bbias

note that the result will be written to output[0...(stop-start-1)]

Reimplemented in CCombinedDotFeatures, and CHashedWDFeaturesTransposed.

Definition at line 67 of file DotFeatures.cpp.

void * dense_dot_range_helper ( void *  p)
staticinherited

Compute the dot product for a range of vectors. This function is called by the threads created in dense_dot_range

Reimplemented in CHashedWDFeaturesTransposed.

Definition at line 231 of file DotFeatures.cpp.

void dense_dot_range_subset ( int32_t *  sub_index,
int32_t  num,
float64_t output,
float64_t alphas,
float64_t vec,
int32_t  dim,
float64_t  b 
)
virtualinherited

Compute the dot product for a subset of vectors. This function makes use of dense_dot alphas[i] * sparse[i]^T * w + b

Parameters
sub_indexindex for which to compute outputs
numlength of index
outputresult for the given vector range
alphasscalars to multiply with, may be NULL
vecdense vector to compute dot product with
dimlength of the dense vector
bbias

Reimplemented in CCombinedDotFeatures, and CHashedWDFeaturesTransposed.

Definition at line 153 of file DotFeatures.cpp.

float64_t dense_dot_sgvec ( int32_t  vec_idx1,
const SGVector< float64_t vec2 
)
virtualinherited

compute dot product between vector1 and a dense vector

Parameters
vec_idx1index of first vector
vec2dense vector

Definition at line 62 of file DotFeatures.cpp.

void display_progress ( int32_t  start,
int32_t  stop,
int32_t  v 
)
protectedinherited

display progress output

Parameters
startminimum value
stopmaximum value
vcurrent value

Definition at line 528 of file DotFeatures.cpp.

float64_t dot ( int32_t  vec_idx1,
CDotFeatures df,
int32_t  vec_idx2 
)
virtual

compute dot product between vector1 and vector2, appointed by their indices

possible with subset of this instance and of DotFeatures

Parameters
vec_idx1index of first vector
dfDotFeatures (of same kind) to compute dot product with
vec_idx2index of second vector

Implements CDotFeatures.

Definition at line 965 of file SparseFeatures.cpp.

CFeatures * duplicate ( ) const
virtual

duplicate feature object

Returns
feature object

Implements CFeatures.

Definition at line 108 of file SparseFeatures.cpp.

void free_feature_iterator ( void *  iterator)
virtual

clean up iterator call this function with the iterator returned by get_first_feature

Parameters
iteratoras returned by get_first_feature

Implements CDotFeatures.

Definition at line 1040 of file SparseFeatures.cpp.

void free_feature_vector ( int32_t  num)

free feature vector

possible with subset

Parameters
numindex of vector in cache

Definition at line 615 of file SparseFeatures.cpp.

void free_sparse_feature_matrix ( )

free sparse feature matrix

any subset is removed

Definition at line 92 of file SparseFeatures.cpp.

void free_sparse_feature_vector ( int32_t  num)

free sparse feature vector

possible with subset

Parameters
numindex of this vector in the cache

Definition at line 354 of file SparseFeatures.cpp.

void free_sparse_features ( )

free sparse feature matrix and cache

any subset is removed

Definition at line 102 of file SparseFeatures.cpp.

int32_t get_cache_size ( ) const
inherited

get cache size

Returns
cache size

Definition at line 203 of file Features.cpp.

float64_t get_combined_feature_weight ( )
inherited

get combined feature weight

Returns
combined feature weight

Definition at line 151 of file DotFeatures.h.

SGMatrix< float64_t > get_computed_dot_feature_matrix ( )
inherited

compute the feature matrix in feature space

Returns
computed feature matrix

Definition at line 284 of file DotFeatures.cpp.

SGVector< float64_t > get_computed_dot_feature_vector ( int32_t  num)
inherited

compute the feature vector in feature space

Returns
computed feature vector

Definition at line 305 of file DotFeatures.cpp.

SGMatrix< float64_t > get_cov ( )
virtualinherited

get covariance

Returns
covariance

Definition at line 427 of file DotFeatures.cpp.

int32_t get_dim_feature_space ( ) const
virtual

obtain the dimensionality of the feature space

(not mix this up with the dimensionality of the input space, usually obtained via get_num_features())

Returns
dimensionality

Implements CDotFeatures.

Definition at line 960 of file SparseFeatures.cpp.

ST get_feature ( int32_t  num,
int32_t  index 
)

get a single feature

possible with subset

Parameters
numnumber of feature vector to retrieve
indexindex of feature in this vector
Returns
sum of features that match dimension index and 0 if none is found

Definition at line 113 of file SparseFeatures.cpp.

EFeatureClass get_feature_class ( ) const
virtual

get feature class

Returns
feature class SPARSE

Implements CFeatures.

Definition at line 610 of file SparseFeatures.cpp.

void * get_feature_iterator ( int32_t  vector_index)
virtual

iterate over the non-zero features

call get_feature_iterator first, followed by get_next_feature and free_feature_iterator to cleanup

possible with subset

Parameters
vector_indexthe index of the vector over whose components to iterate over
Returns
feature iterator (to be passed to get_next_feature)

Implements CDotFeatures.

Definition at line 1007 of file SparseFeatures.cpp.

virtual EFeatureType get_feature_type ( ) const
virtual

get feature type

Returns
templated feature type

Implements CFeatures.

SGMatrix< ST > get_full_feature_matrix ( )

gets a copy of a full feature matrix

possible with subset

Returns
full dense feature matrix

Definition at line 453 of file SparseFeatures.cpp.

ST * get_full_feature_vector ( int32_t  num,
int32_t &  len 
)

converts a sparse feature vector into a dense one preprocessed compute_feature_vector caller cleans up

Parameters
numindex of feature vector
lenlength is returned by reference
Returns
dense feature vector

Definition at line 134 of file SparseFeatures.cpp.

SGVector< ST > get_full_feature_vector ( int32_t  num)

get the fully expanded dense feature vector num

Returns
dense feature vector
Parameters
numindex of feature vector

Definition at line 158 of file SparseFeatures.cpp.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 224 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 259 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 272 of file SGObject.cpp.

SGVector< float64_t > get_mean ( )
virtualinherited

get mean

Returns
mean returned

Definition at line 384 of file DotFeatures.cpp.

SGVector< float64_t > get_mean ( CDotFeatures lhs,
CDotFeatures rhs 
)
staticinherited

get mean of two CDotFeature objects

Returns
mean returned

Definition at line 402 of file DotFeatures.cpp.

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

Definition at line 1108 of file SGObject.cpp.

char * get_modsel_param_descr ( const char *  param_name)
inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

Parameters
param_namename of the parameter
Returns
description of the parameter

Definition at line 1132 of file SGObject.cpp.

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

Parameters
param_namename of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1145 of file SGObject.cpp.

virtual const char* get_name ( ) const
virtual
Returns
object name

Implements CSGObject.

Definition at line 524 of file SparseFeatures.h.

bool get_next_feature ( int32_t &  index,
float64_t value,
void *  iterator 
)
virtual

iterate over the non-zero features

call this function with the iterator returned by get_first_feature and call free_feature_iterator to cleanup

Parameters
indexis returned by reference (-1 when not available)
valueis returned by reference
iteratoras returned by get_first_feature
Returns
true if a new non-zero feature got returned

Implements CDotFeatures.

Definition at line 1026 of file SparseFeatures.cpp.

int32_t get_nnz_features_for_vector ( int32_t  num)
virtual

get number of non-zero features in vector

Parameters
numwhich vector
Returns
number of non-zero features in vector

Implements CDotFeatures.

Definition at line 184 of file SparseFeatures.cpp.

int32_t get_num_features ( )

get number of features

Returns
number of features

Definition at line 597 of file SparseFeatures.cpp.

int64_t get_num_nonzero_entries ( )

get number of non-zero entries in sparse feature matrix

Returns
number of non-zero entries in sparse feature matrix

Definition at line 623 of file SparseFeatures.cpp.

int32_t get_num_preprocessed ( ) const
inherited

get whether specified preprocessor (or all if num=1) was/were already applied

get the number of applied preprocs

Returns
number of applied preprocessors

Definition at line 123 of file Features.cpp.

int32_t get_num_preprocessors ( ) const
inherited

get number of preprocessors

Returns
number of preprocessors

Definition at line 198 of file Features.cpp.

int32_t get_num_vectors ( ) const
virtual

get number of feature vectors, possibly of subset

Returns
number of feature vectors

Implements CFeatures.

Definition at line 592 of file SparseFeatures.cpp.

CPreprocessor * get_preprocessor ( int32_t  num) const
inherited

get current preprocessor

get specified preprocessor

Parameters
numindex of preprocessor in list

Definition at line 111 of file Features.cpp.

int32_t get_size ( ) const
virtual

get memory footprint of one feature

Returns
memory footprint of one feature

Implements CFeatures.

Definition at line 579 of file SparseFeatures.cpp.

SGSparseVector< ST > * get_sparse_feature_matrix ( int32_t &  num_feat,
int32_t &  num_vec 
)

get the pointer to the sparse feature matrix num_feat,num_vectors are returned by reference

not possible with subset

Parameters
num_featnumber of features in matrix
num_vecnumber of vectors in matrix
Returns
feature matrix

Definition at line 362 of file SparseFeatures.cpp.

SGSparseMatrix< ST > get_sparse_feature_matrix ( )

get the sparse feature matrix

not possible with subset

Returns
sparse matrix

Definition at line 373 of file SparseFeatures.cpp.

SGSparseVector< ST > get_sparse_feature_vector ( int32_t  num)

get sparse feature vector for sample num from the matrix as it is if matrix is initialized, else return preprocessed compute_feature_vector

possible with subset

Parameters
numindex of feature vector
Returns
sparse feature vector

Definition at line 192 of file SparseFeatures.cpp.

CSubsetStack * get_subset_stack ( )
virtualinherited

returns subset stack

Returns
subset stack

Definition at line 369 of file Features.cpp.

CSparseFeatures< ST > * get_transposed ( )

get a transposed copy of the features

possible with subset

Returns
transposed copy

Definition at line 383 of file SparseFeatures.cpp.

SGSparseVector< ST > * get_transposed ( int32_t &  num_feat,
int32_t &  num_vec 
)

compute and return the transpose of the sparse feature matrix which will be prepocessed. num_feat, num_vectors are returned by reference caller has to clean up

possible with subset

Parameters
num_featnumber of features in matrix
num_vecnumber of vectors in matrix
Returns
transposed sparse feature matrix

Definition at line 392 of file SparseFeatures.cpp.

bool has_property ( EFeatureProperty  p) const
inherited

check if features have given property

Parameters
pfeature property
Returns
if features have given property

Definition at line 336 of file Features.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 278 of file SGObject.cpp.

bool is_preprocessed ( int32_t  num) const
inherited

get whether specified preprocessor was already applied

Parameters
numindex of preprocessor in list

Definition at line 193 of file Features.cpp.

void list_feature_obj ( ) const
inherited

list feature object

Definition at line 214 of file Features.cpp.

void load ( CFile loader)
virtual

load features from file

any subset is removed before

Parameters
loaderFile object to load data from

Reimplemented from CFeatures.

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

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

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

Definition at line 679 of file SGObject.cpp.

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

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

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

Definition at line 523 of file SGObject.cpp.

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

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

Parameters
filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Reimplemented in CModelSelectionParameters.

Definition at line 354 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 in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CANOVAKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 1033 of file SGObject.cpp.

void load_serializable_pre ( ) throw (ShogunException)
protectedvirtualinherited

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

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Definition at line 1028 of file SGObject.cpp.

CRegressionLabels * load_svmlight_file ( char *  fname,
bool  do_sort_features = true 
)

load features from file

any subset is removed before

Parameters
fnamefilename to load from
do_sort_featuresif true features will be sorted to ensure they are in ascending order
Returns
label object with corresponding labels

Definition at line 712 of file SparseFeatures.cpp.

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

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

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

Definition at line 717 of file SGObject.cpp.

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

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

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

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

Definition at line 923 of file SGObject.cpp.

bool obtain_from_simple ( CDenseFeatures< ST > *  sf)

obtain sparse features from simple features

subset on input is ignored, subset of this instance is removed

Parameters
sfsimple features
Returns
if obtaining was successful

Definition at line 584 of file SparseFeatures.cpp.

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

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

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

Definition at line 864 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1084 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 290 of file SGObject.cpp.

void remove_all_subsets ( )
virtualinherited

removes all subsets Calls subset_changed_post() afterwards

Reimplemented in CCombinedFeatures.

Definition at line 363 of file Features.cpp.

void remove_subset ( )
virtualinherited

removes that last added subset from subset stack, if existing Calls subset_changed_post() afterwards

Reimplemented in CCombinedFeatures.

Definition at line 357 of file Features.cpp.

bool reshape ( int32_t  num_features,
int32_t  num_vectors 
)
virtualinherited

in case there is a feature matrix allow for reshaping

NOT IMPLEMENTED!

Parameters
num_featuresnew number of features
num_vectorsnew number of vectors
Returns
if reshaping was successful

Reimplemented in CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, and CDenseFeatures< uint16_t >.

Definition at line 208 of file Features.cpp.

void save ( CFile writer)
virtual

save features to file

not possible with subset

Parameters
writerFile object to write data to

Reimplemented from CFeatures.

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

Save this object to file.

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

Reimplemented in CModelSelectionParameters.

Definition at line 296 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 in CKernel.

Definition at line 1043 of file SGObject.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 in CKernel.

Definition at line 1038 of file SGObject.cpp.

void set_combined_feature_weight ( float64_t  nw)
inherited

set combined kernel weight

Parameters
nwnew combined feature weight

Definition at line 157 of file DotFeatures.h.

bool set_full_feature_matrix ( SGMatrix< ST >  full)
virtual

creates a sparse feature matrix from a full dense feature matrix necessary to set feature_matrix, num_features and num_vectors where num_features is the column offset, and columns are linear in memory see above for definition of sparse_feature_matrix

any subset is removed before

Parameters
fullfull feature matrix

Definition at line 477 of file SparseFeatures.cpp.

void set_generic< floatmax_t > ( )
inherited

set generic type to T

Definition at line 41 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 217 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 230 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 265 of file SGObject.cpp.

int32_t set_num_features ( int32_t  num)

set number of features

Sometimes when loading sparse features not all possible dimensions are used. This may pose a problem to classifiers when being applied to higher dimensional test-data. This function allows to artificially explode the feature space

Parameters
numthe number of features, must be larger than the current number of features
Returns
previous number of features

Definition at line 602 of file SparseFeatures.cpp.

void set_preprocessed ( int32_t  num)
inherited

set applied flag for preprocessor

Parameters
numindex of preprocessor in list

Definition at line 188 of file Features.cpp.

void set_property ( EFeatureProperty  p)
inherited

set property

Parameters
pkernel property to set

Definition at line 341 of file Features.cpp.

void set_sparse_feature_matrix ( SGSparseMatrix< ST >  sm)

set sparse feature matrix

not possible with subset

Parameters
smsparse feature matrix

Definition at line 436 of file SparseFeatures.cpp.

virtual 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 122 of file SGObject.h.

void sort_features ( )

ensure that features occur in ascending order, only call when no preprocessors are attached

not possiblwe with subset

Definition at line 878 of file SparseFeatures.cpp.

ST sparse_dot ( ST  alpha,
SGSparseVectorEntry< ST > *  avec,
int32_t  alen,
SGSparseVectorEntry< ST > *  bvec,
int32_t  blen 
)
static

compute the dot product between two sparse feature vectors alpha * vec^T * vec

Parameters
alphascalar to multiply with
avecfirst sparse feature vector
alenavec's length
bvecsecond sparse feature vector
blenbvec's length
Returns
dot product between the two sparse feature vectors

Definition at line 251 of file SparseFeatures.cpp.

virtual void subset_changed_post ( )
virtualinherited

method may be overwritten to update things that depend on subset

Reimplemented in CStringFeatures< ST >, CStringFeatures< T >, CStringFeatures< uint8_t >, CStringFeatures< char >, and CStringFeatures< uint16_t >.

Definition at line 262 of file Features.h.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 285 of file SGObject.cpp.

void unset_property ( EFeatureProperty  p)
inherited

unset property

Parameters
pkernel property to unset

Definition at line 346 of file Features.cpp.

bool update_parameter_hash ( )
protectedvirtualinherited

Updates the hash of current parameter combination.

Returns
bool if parameter combination has changed since last update.

Definition at line 237 of file SGObject.cpp.

bool write_svmlight_file ( char *  fname,
CRegressionLabels label 
)

write features to file using svm light format

not possible with subset

Parameters
fnamefilename to write to
labelLabel object (number of labels must correspond to number of features)
Returns
true if successful

Definition at line 923 of file SparseFeatures.cpp.

Member Data Documentation

float64_t combined_weight
protectedinherited

feature weighting in combined dot features

Definition at line 246 of file DotFeatures.h.

CCache< SGSparseVectorEntry<ST> >* feature_cache
protected

feature cache

Definition at line 555 of file SparseFeatures.h.

SGIO* io
inherited

io

Definition at line 462 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 480 of file SGObject.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 474 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 477 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 471 of file SGObject.h.

CSubsetStack* m_subset_stack
protectedinherited

subset used for index transformations

Definition at line 296 of file Features.h.

int32_t num_features
protected

total number of features

Definition at line 549 of file SparseFeatures.h.

int32_t num_vectors
protected

total number of vectors

Definition at line 546 of file SparseFeatures.h.

Parallel* parallel
inherited

parallel

Definition at line 465 of file SGObject.h.

SGSparseVector<ST>* sparse_feature_matrix
protected

array of sparse vectors of size num_vectors

Definition at line 552 of file SparseFeatures.h.

Version* version
inherited

version

Definition at line 468 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation