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CFeatureSelection< ST > Class Template Referenceabstract

Detailed Description

template<class ST>
class shogun::CFeatureSelection< ST >

Template class CFeatureSelection, base class for all feature selection preprocessors which select a subset of features (dimensions in the feature matrix) to achieve a specified number of dimensions, m_target_dim from a given set of features. This class showcases all feature selection algorithms via a generic interface. Supported algorithms are specified by the enum EFeatureSelectionAlgorithm which can be set via set_algorithm() call. Supported wrapper algorithms are.

Since all these algorithm cannot be applied for all the feature selection approaches, the method set_algorithm() is kept abstract which is defined in the subclasses as appropriate.

The apply() method acts as a wrapper which decides which above methods to call based on the algorithm specified by m_algorithm. This method makes a deep copy of the original feature object using CSGObject::clone and then performs feature selection on it. The actual memory requirement depends on how copying a dimension subset is handled in CFeatures::copy_dimension_subset implementation.

For computing the measures that are used to rank the features for feature selection task, it relies on an abstract method compute_measures() which is defined in the subclasses.

Due to the difference in the measure, the removal policy for features can be different which is specified by the EFeatureRemovalPolicy enum and can be set by set_policy() call. The supported policies are

Note that not all policies can be adapted for a specific feature seleciton approaches. In general, in classes where feature selection is performed by removing the features which correspond to lowest measure, the policies shogun::N_SMALLEST and shogun::PERCENTILE_SMALLEST are appropriate. When features corresponding to highest measures are removed (e.g. training error in a cross-validation scenario), shogun::N_LARGEST and shogun::PERCENTILE_LARGEST are applicable. Therefore, set_policy() is kept abstract and subclasses define this to allow specific policies to be set.

Removal of features in each iteration is handled by an abstract method remove_feats() that removes a set of features at once based on the ranks of the features on the measure. Internally this method also updates a subset stack to keep track of the selected features. After calling apply(), the indices of the original features that are selected can be obtained by calling get_selected_feats() method. Please note that the selected features are always kept in the original order.

Some of the methods are for internal purpose and are not exposed to the public API. For example,

Definition at line 139 of file FeatureSelection.h.

Inheritance diagram for CFeatureSelection< ST >:
[legend]

Public Member Functions

 CFeatureSelection ()
 
virtual ~CFeatureSelection ()
 
virtual CFeaturesapply (CFeatures *features)
 
virtual float64_t compute_measures (CFeatures *features, index_t idx)=0
 
virtual CFeaturesremove_feats (CFeatures *features, SGVector< index_t > argsorted)=0
 
SGVector< index_tget_selected_feats ()
 
virtual EFeatureClass get_feature_class ()
 
virtual EFeatureType get_feature_type ()
 
virtual EPreprocessorType get_type () const
 
void set_target_dim (index_t target_dim)
 
index_t get_target_dim () const
 
virtual void set_algorithm (EFeatureSelectionAlgorithm algorithm)=0
 
EFeatureSelectionAlgorithm get_algorithm () const
 
virtual void set_policy (EFeatureRemovalPolicy policy)=0
 
EFeatureRemovalPolicy get_policy () const
 
void set_num_remove (index_t num_remove)
 
index_t get_num_remove () const
 
virtual void set_labels (CLabels *labels)
 
CLabelsget_labels () const
 
virtual void cleanup ()
 
virtual const char * get_name () const
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
template<>
EFeatureType get_feature_type ()
 
virtual bool init (CFeatures *features)=0
 
virtual CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
 
void set_global_io (SGIO *io)
 
SGIOget_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallelget_global_parallel ()
 
void set_global_version (Version *version)
 
Versionget_global_version ()
 
SGStringList< char > get_modelsel_names ()
 
void print_modsel_params ()
 
char * get_modsel_param_descr (const char *param_name)
 
index_t get_modsel_param_index (const char *param_name)
 
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
 
bool has (const std::string &name) const
 
template<typename T >
bool has (const Tag< T > &tag) const
 
template<typename T , typename U = void>
bool has (const std::string &name) const
 
template<typename T >
void set (const Tag< T > &_tag, const T &value)
 
template<typename T , typename U = void>
void set (const std::string &name, const T &value)
 
template<typename T >
get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
get (const std::string &name) const
 
virtual void update_parameter_hash ()
 
virtual bool parameter_hash_changed ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
 
virtual CSGObjectclone ()
 

Public Attributes

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

virtual CFeaturesapply_backward_elimination (CFeatures *features)
 
virtual void precompute ()
 
virtual void adapt_params (CFeatures *features)
 
index_t get_num_features (CFeatures *features) const
 
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)
 
template<typename T >
void register_param (Tag< T > &_tag, const T &value)
 
template<typename T >
void register_param (const std::string &name, const T &value)
 

Protected Attributes

index_t m_target_dim
 
EFeatureSelectionAlgorithm m_algorithm
 
EFeatureRemovalPolicy m_policy
 
index_t m_num_remove
 
CLabelsm_labels
 
CSubsetStackm_subset
 

Constructor & Destructor Documentation

Default constructor

Definition at line 43 of file FeatureSelection.cpp.

~CFeatureSelection ( )
virtual

Destructor

Definition at line 73 of file FeatureSelection.cpp.

Member Function Documentation

void adapt_params ( CFeatures features)
protectedvirtual

Tunes the parameters which are required to compute the measure based on current features. Overridden in the subclasses. Here it does nothing.

Parameters
featuresthe features based on which parameters are needed to be tuned for computing measures

Definition at line 219 of file FeatureSelection.cpp.

CFeatures * apply ( CFeatures features)
virtual

Generic interface for applying the feature selection preprocessor. Acts as a wrapper which decides which actual method to call based on the algorithm specified.

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

Implements CPreprocessor.

Definition at line 173 of file FeatureSelection.cpp.

CFeatures * apply_backward_elimination ( CFeatures features)
protectedvirtual

Applies backward elimination algorithm for performing feature selection. After performing necessary precomputing (defined by subclasses), it iteratively eliminates a number of features based on a measure until target dimension is reached.

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

Definition at line 87 of file FeatureSelection.cpp.

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

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

Parameters
dictdictionary of parameters to be built.

Definition at line 630 of file SGObject.cpp.

void cleanup ( )
virtual

performs cleanup

Implements CPreprocessor.

Definition at line 81 of file FeatureSelection.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 747 of file SGObject.cpp.

virtual float64_t compute_measures ( CFeatures features,
index_t  idx 
)
pure virtual

Abstract method that is defined in the subclasses to compute the measures for the provided features based on which feature selection is performed.

Parameters
featuresthe features on which the measure has to be computed
idxthe index that decides which features should we compute the measure on
Returns
the measure based on which features are selected

Implemented in CDependenceMaximization.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 231 of file SGObject.cpp.

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

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

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

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

Definition at line 651 of file SGObject.cpp.

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

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

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

Definition at line 367 of file SGObject.h.

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

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

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

Definition at line 388 of file SGObject.h.

EFeatureSelectionAlgorithm get_algorithm ( ) const
Returns
the feature removal algorithm being used

Definition at line 283 of file FeatureSelection.cpp.

EFeatureClass get_feature_class ( )
virtual
Returns
the feature class, shogun::C_ANY

Implements CPreprocessor.

Definition at line 322 of file FeatureSelection.cpp.

virtual EFeatureType get_feature_type ( )
virtual
Returns
feature type

Implements CPreprocessor.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 334 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 340 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 346 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 352 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 358 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 364 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 370 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 376 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 382 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 388 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 394 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 400 of file FeatureSelection.cpp.

EFeatureType get_feature_type ( )
virtual
Returns
type of objects preprocessor can deal with

Implements CPreprocessor.

Definition at line 406 of file FeatureSelection.cpp.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 268 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 310 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 323 of file SGObject.cpp.

CLabels * get_labels ( ) const
Returns
the labels

Definition at line 315 of file FeatureSelection.cpp.

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

Definition at line 531 of file SGObject.cpp.

char * get_modsel_param_descr ( const char *  param_name)
inherited

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

Parameters
param_namename of the parameter
Returns
description of the parameter

Definition at line 555 of file SGObject.cpp.

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

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

Definition at line 568 of file SGObject.cpp.

virtual const char* get_name ( ) const
virtual
Returns
the class name

Implements CSGObject.

Reimplemented in CDependenceMaximization, CBAHSIC, and CKernelDependenceMaximization.

Definition at line 254 of file FeatureSelection.h.

index_t get_num_features ( CFeatures features) const
protected

Returns the number of features of the provided feature object. Since the number of features doesn't make sense for all types of features, this helper method checks whether obtaining a num_features is possible and then calls get_num_features() on those features after proper type-cast

Parameters
featuresthe feature object
Returns
the number of features

Definition at line 241 of file FeatureSelection.cpp.

index_t get_num_remove ( ) const
Returns
number or percentage of features removed in each iteration

Definition at line 301 of file FeatureSelection.cpp.

EFeatureRemovalPolicy get_policy ( ) const
Returns
the feature removal policy being used

Definition at line 289 of file FeatureSelection.cpp.

SGVector< index_t > get_selected_feats ( )
Returns
indices of selected features

Definition at line 224 of file FeatureSelection.cpp.

index_t get_target_dim ( ) const
Returns
the target dimension

Definition at line 277 of file FeatureSelection.cpp.

EPreprocessorType get_type ( ) const
virtual
Returns
the preprocessor type

Implements CPreprocessor.

Reimplemented in CBAHSIC.

Definition at line 328 of file FeatureSelection.cpp.

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

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

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

Definition at line 289 of file SGObject.h.

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

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

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

Definition at line 301 of file SGObject.h.

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

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

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

Definition at line 312 of file SGObject.h.

virtual bool init ( CFeatures features)
pure virtualinherited
bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

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

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

Definition at line 329 of file SGObject.cpp.

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

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

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

Definition at line 402 of file SGObject.cpp.

void load_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

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

Exceptions
ShogunExceptionwill be thrown if an error occurs.

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

Definition at line 459 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 454 of file SGObject.cpp.

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

Definition at line 295 of file SGObject.cpp.

void precompute ( )
protectedvirtual

Performs the tasks which can be computed beforehand before the actual algorithm begins. This method is overridden in the subclasses. Here it does nothing.

Reimplemented in CKernelDependenceMaximization.

Definition at line 214 of file FeatureSelection.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 507 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 341 of file SGObject.cpp.

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

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

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 439 of file SGObject.h.

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

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

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

Definition at line 452 of file SGObject.h.

virtual CFeatures* remove_feats ( CFeatures features,
SGVector< index_t argsorted 
)
pure virtual

Abstract method which is defined in the subclasses to handle the removal of features based on removal policy (see class documentation). This also updates the subset internally for selected features.

Parameters
featuresthe features object from which specific features has to be removed
argsortedthe argsorted features based on their measures, entry at 0 being the index of the feature corresponding to the smallest measure.
Returns
the feature object after removal of features based on the policy

Implemented in CDependenceMaximization.

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

Save this object to file.

Parameters
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
Returns
TRUE if done, otherwise FALSE

Definition at line 347 of file SGObject.cpp.

void save_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

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

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 469 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 464 of file SGObject.cpp.

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

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

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 328 of file SGObject.h.

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

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

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

Definition at line 354 of file SGObject.h.

virtual void set_algorithm ( EFeatureSelectionAlgorithm  algorithm)
pure virtual

Abstract method which is overridden in the subclasses to set accepted feature selection algorithm

Parameters
algorithmthe feature selection algorithm to use

Implemented in CDependenceMaximization, CKernelDependenceMaximization, and CBAHSIC.

void set_generic ( )
inherited

Definition at line 74 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 79 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 84 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 89 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 94 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 99 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 104 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 109 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 114 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 119 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 124 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 129 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 134 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 139 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 144 of file SGObject.cpp.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 261 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 274 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 316 of file SGObject.cpp.

void set_labels ( CLabels labels)
virtual

Setter for labels. This method may be overridden in subclasses if necessary to set some additional parameters associated with it. For example, in CDependenceMaximization, we need a feature instance of the labels which is used in the estimator. So this method is overridden there to internally convert the labels to a dense feature object in this set call only

Parameters
labelsthe labels

Reimplemented in CDependenceMaximization.

Definition at line 307 of file FeatureSelection.cpp.

void set_num_remove ( index_t  num_remove)

Use this method to set the number or percentile of features to be removed in each iteration.

Parameters
num_removenumber or percentage of features to be removed in each iteration

Definition at line 295 of file FeatureSelection.cpp.

virtual void set_policy ( EFeatureRemovalPolicy  policy)
pure virtual

Abstract method which is overridden in the subclasses to set accepted feature removal policies based on the measure they use

Parameters
policythe feature removal policy

Implemented in CDependenceMaximization.

void set_target_dim ( index_t  target_dim)
Parameters
target_dimthe target dimension to achieve

Definition at line 271 of file FeatureSelection.cpp.

CSGObject * shallow_copy ( ) const
virtualinherited

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

Reimplemented in CGaussianKernel.

Definition at line 225 of file SGObject.cpp.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 336 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 281 of file SGObject.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 537 of file SGObject.h.

EFeatureSelectionAlgorithm m_algorithm
protected

Wrapper algorithm for feature selection

Definition at line 302 of file FeatureSelection.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 552 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 555 of file SGObject.h.

CLabels* m_labels
protected

The labels for the feature vectors

Definition at line 316 of file FeatureSelection.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 549 of file SGObject.h.

index_t m_num_remove
protected

Number or percentage of features to be removed. When the policy is set as shogun::N_SMALLEST or shogun::N_LARGEST, this number decides how many features in an iteration. For shogun::PERCENTILE_SMALLEST or shogun::PERCENTILE_LARGEST, this decides the percentage of current number of features to be removed in each iteration

Definition at line 313 of file FeatureSelection.h.

Parameter* m_parameters
inherited

parameters

Definition at line 546 of file SGObject.h.

EFeatureRemovalPolicy m_policy
protected

Feature removal policy

Definition at line 305 of file FeatureSelection.h.

CSubsetStack* m_subset
protected

The indices of features that are selected

Definition at line 319 of file FeatureSelection.h.

index_t m_target_dim
protected

Target dimension

Definition at line 299 of file FeatureSelection.h.

Parallel* parallel
inherited

parallel

Definition at line 540 of file SGObject.h.

Version* version
inherited

version

Definition at line 543 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation