SHOGUN
3.2.1
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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 N_SMALLEST and PERCENTILE_SMALLEST are appropriate. When features corresponding to highest measures are removed (e.g. training error in a cross-validation scenario), N_LARGEST and 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.
Some of the methods are for internal purpose and are not exposed to the public API. For example,
Definition at line 134 of file FeatureSelection.h.
Public Attributes | |
SGIO * | io |
Parallel * | parallel |
Version * | version |
Parameter * | m_parameters |
Parameter * | m_model_selection_parameters |
Parameter * | m_gradient_parameters |
ParameterMap * | m_parameter_map |
uint32_t | m_hash |
Protected Member Functions | |
virtual CFeatures * | apply_backward_elimination (CFeatures *features) |
virtual void | precompute () |
virtual void | adapt_params (CFeatures *features) |
index_t | get_num_features (CFeatures *features) const |
virtual TParameter * | migrate (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 | |
index_t | m_target_dim |
EFeatureSelectionAlgorithm | m_algorithm |
EFeatureRemovalPolicy | m_policy |
index_t | m_num_remove |
CLabels * | m_labels |
Default constructor
Definition at line 41 of file FeatureSelection.cpp.
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Destructor
Definition at line 68 of file FeatureSelection.cpp.
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Tunes the parameters which are required to compute the measure based on current features. Overridden in the subclasses. Here it does nothing.
features | the features based on which parameters are needed to be tuned for computing measures |
Definition at line 205 of file FeatureSelection.cpp.
Generic interface for applying the feature selection preprocessor. Acts as a wrapper which decides which actual method to call based on the algorithm specified.
features | the input features |
Implements CPreprocessor.
Definition at line 162 of file FeatureSelection.cpp.
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.
features | the input features |
Definition at line 80 of file FeatureSelection.cpp.
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Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.
dict | dictionary of parameters to be built. |
Definition at line 1185 of file SGObject.cpp.
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Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.
Definition at line 1302 of file SGObject.cpp.
Abstract method that is defined in the subclasses to compute the measures for the provided features based on which feature selection is performed.
features | the features on which the measure has to be computed |
idx | the index that decides which features should we compute the measure on |
Implemented in CDependenceMaximization.
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A deep copy. All the instance variables will also be copied.
Definition at line 146 of file SGObject.cpp.
Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!
May be overwritten but please do with care! Should not be necessary in most cases.
other | object to compare with |
accuracy | accuracy to use for comparison (optional) |
tolerant | allows linient check on float equality (within accuracy) |
Definition at line 1206 of file SGObject.cpp.
EFeatureSelectionAlgorithm get_algorithm | ( | ) | const |
Definition at line 252 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 291 of file FeatureSelection.cpp.
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Implements CPreprocessor.
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Implements CPreprocessor.
Definition at line 303 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 309 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 315 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 321 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 327 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 333 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 339 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 345 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 351 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 357 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 363 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 369 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Definition at line 375 of file FeatureSelection.cpp.
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CLabels * get_labels | ( | ) | const |
Definition at line 284 of file FeatureSelection.cpp.
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Definition at line 1077 of file SGObject.cpp.
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Returns description of a given parameter string, if it exists. SG_ERROR otherwise
param_name | name of the parameter |
Definition at line 1101 of file SGObject.cpp.
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Returns index of model selection parameter with provided index
param_name | name of model selection parameter |
Definition at line 1114 of file SGObject.cpp.
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Implements CSGObject.
Reimplemented in CDependenceMaximization, CBAHSIC, and CKernelDependenceMaximization.
Definition at line 245 of file FeatureSelection.h.
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
features | the feature object |
Definition at line 210 of file FeatureSelection.cpp.
index_t get_num_remove | ( | ) | const |
Definition at line 270 of file FeatureSelection.cpp.
EFeatureRemovalPolicy get_policy | ( | ) | const |
Definition at line 258 of file FeatureSelection.cpp.
index_t get_target_dim | ( | ) | const |
Definition at line 246 of file FeatureSelection.cpp.
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Implements CPreprocessor.
Reimplemented in CBAHSIC.
Definition at line 297 of file FeatureSelection.cpp.
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initialize preprocessor with features
Implemented in CPCA, CDependenceMaximization, CRandomFourierGaussPreproc, CHomogeneousKernelMap, CDimensionReductionPreprocessor, CDecompressString< ST >, CKernelPCA, CPNorm, CLogPlusOne, CNormOne, CPruneVarSubMean, CRescaleFeatures, CSumOne, CSortWordString, and CSortUlongString.
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If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.
generic | set to the type of the generic if returning TRUE |
Definition at line 243 of file SGObject.cpp.
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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)
file_version | parameter version of the file |
current_version | version from which mapping begins (you want to use Version::get_version_parameter() for this in most cases) |
file | file to load from |
prefix | prefix for members |
Definition at line 648 of file SGObject.cpp.
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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
param_info | information of parameter |
file_version | parameter version of the file, must be <= provided parameter version |
file | file to load from |
prefix | prefix for members |
Definition at line 489 of file SGObject.cpp.
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Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!
file | where to load from |
prefix | prefix for members |
param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
Definition at line 320 of file SGObject.cpp.
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Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 1004 of file SGObject.cpp.
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Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 999 of file SGObject.cpp.
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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
param_base | set of TParameter instances that are mapped to the provided target parameter infos |
base_version | version of the parameter base |
target_param_infos | set of SGParamInfo instances that specify the target parameter base |
Definition at line 686 of file SGObject.cpp.
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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
param_base | set of TParameter instances to use for migration |
target | parameter info for the resulting TParameter |
Definition at line 893 of file SGObject.cpp.
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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)
param_base | set of TParameter instances to use for migration |
target | parameter info for the resulting TParameter |
replacement | (used as output) here the TParameter instance which is returned by migration is created into |
to_migrate | the only source that is used for migration |
old_name | with this parameter, a name change may be specified |
Definition at line 833 of file SGObject.cpp.
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Definition at line 209 of file SGObject.cpp.
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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 200 of file FeatureSelection.cpp.
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prints all parameter registered for model selection and their type
Definition at line 1053 of file SGObject.cpp.
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prints registered parameters out
prefix | prefix for members |
Definition at line 255 of file SGObject.cpp.
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Abstract method which is defined in the subclasses to handle the removal of features based on removal policy (see class documentation).
features | the features object from which specific features has to be removed |
argsorted | the argsorted features based on their measures, entry at 0 being the index of the feature corresponding to the smallest measure. |
Implemented in CDependenceMaximization.
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Save this object to file.
file | where to save the object; will be closed during returning if PREFIX is an empty string. |
prefix | prefix for members |
param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
Definition at line 261 of file SGObject.cpp.
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Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel.
Definition at line 1014 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 1009 of file SGObject.cpp.
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Abstract method which is overridden in the subclasses to set accepted feature selection algorithm
algorithm | the feature selection algorithm to use |
Implemented in CDependenceMaximization, CKernelDependenceMaximization, and CBAHSIC.
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Definition at line 38 of file SGObject.cpp.
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Definition at line 43 of file SGObject.cpp.
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Definition at line 48 of file SGObject.cpp.
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Definition at line 53 of file SGObject.cpp.
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Definition at line 58 of file SGObject.cpp.
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Definition at line 63 of file SGObject.cpp.
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Definition at line 68 of file SGObject.cpp.
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Definition at line 73 of file SGObject.cpp.
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Definition at line 78 of file SGObject.cpp.
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Definition at line 83 of file SGObject.cpp.
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Definition at line 88 of file SGObject.cpp.
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Definition at line 93 of file SGObject.cpp.
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Definition at line 98 of file SGObject.cpp.
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Definition at line 103 of file SGObject.cpp.
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Definition at line 108 of file SGObject.cpp.
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set generic type to T
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set the parallel object
parallel | parallel object to use |
Definition at line 189 of file SGObject.cpp.
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set the version object
version | version object to use |
Definition at line 230 of file SGObject.cpp.
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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
labels | the labels |
Reimplemented in CDependenceMaximization.
Definition at line 276 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.
num_remove | number or percentage of features to be removed in each iteration |
Definition at line 264 of file FeatureSelection.cpp.
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Abstract method which is overridden in the subclasses to set accepted feature removal policies based on the measure they use
policy | the feature removal policy |
Implemented in CDependenceMaximization.
void set_target_dim | ( | index_t | target_dim | ) |
target_dim | the target dimension to achieve |
Definition at line 240 of file FeatureSelection.cpp.
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A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
Reimplemented in CGaussianKernel.
Definition at line 140 of file SGObject.cpp.
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unset generic type
this has to be called in classes specializing a template class
Definition at line 250 of file SGObject.cpp.
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Updates the hash of current parameter combination
Definition at line 196 of file SGObject.cpp.
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io
Definition at line 461 of file SGObject.h.
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Wrapper algorithm for feature selection
Definition at line 293 of file FeatureSelection.h.
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parameters wrt which we can compute gradients
Definition at line 476 of file SGObject.h.
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Hash of parameter values
Definition at line 482 of file SGObject.h.
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The labels for the feature vectors
Definition at line 307 of file FeatureSelection.h.
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model selection parameters
Definition at line 473 of file SGObject.h.
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Number or percentage of features to be removed. When the policy is set as N_SMALLEST or N_LARGEST, this number decides how many features in an iteration. For PERCENTILE_SMALLEST or PERCENTILE_LARGEST, this decides the percentage of current number of features to be removed in each iteration
Definition at line 304 of file FeatureSelection.h.
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map for different parameter versions
Definition at line 479 of file SGObject.h.
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parameters
Definition at line 470 of file SGObject.h.
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Feature removal policy
Definition at line 296 of file FeatureSelection.h.
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Target dimension
Definition at line 290 of file FeatureSelection.h.
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parallel
Definition at line 464 of file SGObject.h.
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version
Definition at line 467 of file SGObject.h.