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CRandomFourierGaussPreproc Class Reference

Detailed Description

Preprocessor CRandomFourierGaussPreproc implements Random Fourier Features for the Gauss kernel a la Ali Rahimi and Ben Recht Nips2007 after preprocessing the features using them in a linear kernel approximates a gaussian kernel.

approximation quality depends on dimension of feature space, NOT on number of data.

effectively it requires two parameters for initialization: (A) the dimension of the input features stored in dim_input_space (B) the dimension of the output feature space

in order to make it work there are two ways: (1) if you have already previously computed random fourier features which you want to use together with newly computed ones, then you have to take the random coefficients from the previous computation and provide them via void set_randomcoefficients(...) for the new computation this case is important for example if you compute separately features on training and testing data in two feature objects

in this case you have to set 1a) void set_randomcoefficients(...)

(2) if you compute random fourier features from scratch in this case you have to set 2a) set_kernelwidth(...) 2b) void set_dim_feature_space(const int32_t dim); 2c) set_dim_input_space(const int32_t dim); 2d) init_randomcoefficients() or apply_to_feature_matrix(...)

Definition at line 51 of file RandomFourierGaussPreproc.h.

Inheritance diagram for CRandomFourierGaussPreproc:
Inheritance graph
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Public Member Functions

 CRandomFourierGaussPreproc ()
 CRandomFourierGaussPreproc (const CRandomFourierGaussPreproc &pr)
 ~CRandomFourierGaussPreproc ()
virtual SGMatrix< float64_tapply_to_feature_matrix (CFeatures *features)
virtual SGVector< float64_tapply_to_feature_vector (SGVector< float64_t > vector)
virtual EFeatureType get_feature_type ()
virtual EFeatureClass get_feature_class ()
virtual bool init (CFeatures *f)
void set_kernelwidth (const float64_t width)
float64_t get_kernelwidth () const
void get_randomcoefficients (float64_t **randomcoeff_additive2, float64_t **randomcoeff_multiplicative2, int32_t *dim_feature_space2, int32_t *dim_input_space2, float64_t *kernelwidth2) const
void set_randomcoefficients (float64_t *randomcoeff_additive2, float64_t *randomcoeff_multiplicative2, const int32_t dim_feature_space2, const int32_t dim_input_space2, const float64_t kernelwidth2)
void set_dim_input_space (const int32_t dim)
void set_dim_feature_space (const int32_t dim)
bool init_randomcoefficients ()
int32_t get_dim_input_space () const
int32_t get_dim_feature_space () const
void cleanup ()
virtual const char * get_name () const
 return the name of the preprocessor
virtual EPreprocessorType get_type () const
 return a type of preprocessor
virtual CFeaturesapply (CFeatures *features)
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::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 ()

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

void copy (const CRandomFourierGaussPreproc &feats)
bool test_rfinited () const
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)

Protected Attributes

float64_t kernelwidth
float64_t cur_kernelwidth
int32_t dim_input_space
int32_t cur_dim_input_space
int32_t dim_feature_space
int32_t cur_dim_feature_space
float64_trandomcoeff_additive
float64_trandomcoeff_multiplicative

Constructor & Destructor Documentation

default constructor

Definition at line 62 of file RandomFourierGaussPreproc.cpp.

alternative constructor

Definition at line 97 of file RandomFourierGaussPreproc.cpp.

default destructor takes care for float64_t* randomcoeff_additive,float64_t* randomcoeff_multiplicative;

Definition at line 127 of file RandomFourierGaussPreproc.cpp.

Member Function Documentation

virtual CFeatures* apply ( CFeatures features)
virtualinherited

generic interface for applying the preprocessor. used as a wrapper for apply_to_feature_matrix() method

Parameters
featuresthe dense input features
Returns
the result feature object after applying the preprocessor

Implements CPreprocessor.

SGMatrix< float64_t > apply_to_feature_matrix ( CFeatures features)
virtual

default processing routine, inherited from base class

Parameters
featuresthe features to be processed, must be of type CDenseFeatures<float64_t>
Returns
the processed feature matrix from the CDenseFeatures<float64_t> class in case (2) (see description above) this routine requires only steps 2a) and 2b), the rest is determined automatically

Implements CDensePreprocessor< float64_t >.

Definition at line 368 of file RandomFourierGaussPreproc.cpp.

SGVector< float64_t > apply_to_feature_vector ( SGVector< float64_t vector)
virtual

alternative processing routine, inherited from base class

Parameters
vectorthe feature vector to be processed
Returns
processed feature vector in order to work this routine requires the steps described above under cases (1) or two (2) before calling this routine

Implements CDensePreprocessor< float64_t >.

Definition at line 350 of file RandomFourierGaussPreproc.cpp.

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

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

Parameters
dictdictionary of parameters to be built.

Definition at line 1243 of file SGObject.cpp.

void cleanup ( )
virtual

inherited from base class does nothing

Implements CPreprocessor.

Definition at line 411 of file RandomFourierGaussPreproc.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 1360 of file SGObject.cpp.

void copy ( const CRandomFourierGaussPreproc feats)
protected

helper for copy constructor and assignment operator=

Definition at line 17 of file RandomFourierGaussPreproc.cpp.

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

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

Parameters
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 1264 of file SGObject.cpp.

int32_t get_dim_feature_space ( ) const

a getter

Returns
the set value of protected member dim_feature_space

Definition at line 142 of file RandomFourierGaussPreproc.cpp.

int32_t get_dim_input_space ( ) const

a getter

Returns
the set value of protected member dim_input_space

Definition at line 156 of file RandomFourierGaussPreproc.cpp.

EFeatureClass get_feature_class ( )
virtual

inherited from base class

Returns
F_DREAL

Reimplemented from CDensePreprocessor< float64_t >.

Definition at line 134 of file RandomFourierGaussPreproc.cpp.

EFeatureType get_feature_type ( )
virtual

inherited from base class

Returns
C_DENSE

Reimplemented from CDensePreprocessor< float64_t >.

Definition at line 138 of file RandomFourierGaussPreproc.cpp.

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 278 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 291 of file SGObject.cpp.

float64_t get_kernelwidth ( ) const

getter for kernel width

Returns
kernel width throws exception if kernelwidth <=0

Definition at line 168 of file RandomFourierGaussPreproc.cpp.

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

Definition at line 1135 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 1159 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 1172 of file SGObject.cpp.

virtual const char* get_name ( ) const
virtual

return the name of the preprocessor

Implements CSGObject.

Definition at line 171 of file RandomFourierGaussPreproc.h.

void get_randomcoefficients ( float64_t **  randomcoeff_additive2,
float64_t **  randomcoeff_multiplicative2,
int32_t *  dim_feature_space2,
int32_t *  dim_input_space2,
float64_t kernelwidth2 
) const

getter for the random coefficients necessary for creating random fourier features compatible to the current ones returns values of internal members randomcoeff_additive and randomcoeff_multiplicative

Definition at line 256 of file RandomFourierGaussPreproc.cpp.

virtual EPreprocessorType get_type ( ) const
virtual

return a type of preprocessor

Reimplemented from CDensePreprocessor< float64_t >.

Definition at line 174 of file RandomFourierGaussPreproc.h.

bool init ( CFeatures f)
virtual

initializer routine calls set_dim_input_space(const int32_t dim); with the proper value calls init_randomcoefficients(); this call does NOT override a previous call to void set_randomcoefficients(...) IF and ONLY IF the dimensions of input AND feature space are equal to the values from the previous call to void set_randomcoefficients(...)

Parameters
fthe features to be processed, must be of type CDenseFeatures<float64_t>
Returns
true if new random coefficients were generated, false if old ones from a call to set_randomcoefficients(...) are kept

Implements CPreprocessor.

Definition at line 318 of file RandomFourierGaussPreproc.cpp.

bool init_randomcoefficients ( )

computes new random coefficients IF test_rfinited() evaluates to false test_rfinited() evaluates to TRUE if void set_randomcoefficients(...) hase been called and the values set by set_dim_input_space(...) , set_dim_feature_space(...) and set_kernelwidth(...) are consistent to the call of void set_randomcoefficients(...)

throws shogun exception if dim_feature_space <= 0 or dim_input_space <= 0

Returns
returns true if test_rfinited() evaluates to false and new coefficients are computed returns false if test_rfinited() evaluates to true and old random coefficients are kept which were set by a previous call to void set_randomcoefficients(...)

this function is useful if you want to use apply_to_feature_vector but cannot call before it init(CFeatures *f)

Definition at line 198 of file RandomFourierGaussPreproc.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 297 of file SGObject.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_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_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 704 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 545 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
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

Definition at line 374 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 occurs.

Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 1062 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 occurs.

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

Definition at line 1057 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_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 742 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 949 of file SGObject.cpp.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
)
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 889 of file SGObject.cpp.

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

Definition at line 263 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1111 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 309 of file SGObject.cpp.

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

Definition at line 315 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 occurs.

Reimplemented in CKernel.

Definition at line 1072 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 occurs.

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

Definition at line 1067 of file SGObject.cpp.

void set_dim_feature_space ( const int32_t  dim)

a setter

Parameters
dimthe value of protected member dim_feature_space throws a shogun exception if dim<=0

Definition at line 146 of file RandomFourierGaussPreproc.cpp.

void set_dim_input_space ( const int32_t  dim)

a setter

Parameters
dimthe value of protected member dim_input_space throws a shogun exception if dim<=0

Definition at line 172 of file RandomFourierGaussPreproc.cpp.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 42 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 230 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 243 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 284 of file SGObject.cpp.

void set_kernelwidth ( const float64_t  width)

setter for kernel width

Parameters
widthkernel width to be set

Definition at line 160 of file RandomFourierGaussPreproc.cpp.

void set_randomcoefficients ( float64_t randomcoeff_additive2,
float64_t randomcoeff_multiplicative2,
const int32_t  dim_feature_space2,
const int32_t  dim_input_space2,
const float64_t  kernelwidth2 
)

setter for the random coefficients necessary for creating random fourier features compatible to the previous ones sets values of internal members randomcoeff_additive and randomcoeff_multiplicative simply use as input what you got from get_random_coefficients(...)

Definition at line 288 of file RandomFourierGaussPreproc.cpp.

CSGObject * shallow_copy ( ) const
virtualinherited

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

Reimplemented in CGaussianKernel.

Definition at line 194 of file SGObject.cpp.

bool test_rfinited ( ) const
protected

tests whether rf features have already been initialized

Definition at line 182 of file RandomFourierGaussPreproc.cpp.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 304 of file SGObject.cpp.

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 cur_dim_feature_space
protected

actual dimension of output features as set by bool init_randomcoefficients() or void set_randomcoefficients

Definition at line 213 of file RandomFourierGaussPreproc.h.

int32_t cur_dim_input_space
protected

actual dimension of input features as set by bool init_randomcoefficients() or void set_randomcoefficients

Definition at line 202 of file RandomFourierGaussPreproc.h.

float64_t cur_kernelwidth
protected

dimension of input features width of gaussian kernel in the form of exp(-x^2 / (2.0 kernelwidth^2) ) NOTE the 2.0 and the power ^2 !

Definition at line 192 of file RandomFourierGaussPreproc.h.

int32_t dim_feature_space
protected

desired dimension of output features as set by void set_dim_feature_space(const int32_t dim)

Definition at line 208 of file RandomFourierGaussPreproc.h.

int32_t dim_input_space
protected

desired dimension of input features as set by void set_dim_input_space(const int32_t dim)

Definition at line 197 of file RandomFourierGaussPreproc.h.

SGIO* io
inherited

io

Definition at line 496 of file SGObject.h.

float64_t kernelwidth
protected

dimension of input features width of gaussian kernel in the form of exp(-x^2 / (2.0 kernelwidth^2) ) NOTE the 2.0 and the power ^2 !

Definition at line 187 of file RandomFourierGaussPreproc.h.

Parameter* m_gradient_parameters
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.

Parallel* parallel
inherited

parallel

Definition at line 499 of file SGObject.h.

float64_t* randomcoeff_additive
protected

random coefficient length = cur_dim_feature_space

Definition at line 224 of file RandomFourierGaussPreproc.h.

float64_t* randomcoeff_multiplicative
protected

random coefficient length = cur_dim_feature_space* cur_dim_input_space

Definition at line 230 of file RandomFourierGaussPreproc.h.

Version* version
inherited

version

Definition at line 502 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation