SHOGUN
4.1.0
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Class CKernelDependenceMaximization, that uses an implementation of CKernelIndependenceTest to compute dependence measures for feature selection. Different kernels are used for labels and data. For the sake of computational convenience, the precompute() method is overridden to precompute the kernel for labels and save as an instance of CCustomKernel.
Definition at line 49 of file KernelDependenceMaximization.h.
Public Member Functions | |
CKernelDependenceMaximization () | |
virtual | ~CKernelDependenceMaximization () |
void | set_kernel_features (CKernel *kernel) |
CKernel * | get_kernel_features () const |
void | set_kernel_labels (CKernel *kernel) |
CKernel * | get_kernel_labels () const |
virtual void | set_algorithm (EFeatureSelectionAlgorithm algorithm)=0 |
virtual const char * | get_name () const |
virtual float64_t | compute_measures (CFeatures *features, index_t idx) |
virtual CFeatures * | remove_feats (CFeatures *features, SGVector< index_t > ranks) |
virtual void | set_policy (EFeatureRemovalPolicy policy) |
virtual bool | init (CFeatures *features) |
virtual void | set_labels (CLabels *labels) |
virtual CFeatures * | apply (CFeatures *features) |
SGVector< index_t > | get_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 |
EFeatureSelectionAlgorithm | get_algorithm () const |
EFeatureRemovalPolicy | get_policy () const |
void | set_num_remove (index_t num_remove) |
index_t | get_num_remove () const |
CLabels * | get_labels () const |
virtual void | cleanup () |
virtual CSGObject * | shallow_copy () const |
virtual CSGObject * | deep_copy () const |
virtual bool | is_generic (EPrimitiveType *generic) const |
template<class T > | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
template<> | |
void | set_generic () |
void | unset_generic () |
virtual void | print_serializable (const char *prefix="") |
virtual bool | save_serializable (CSerializableFile *file, const char *prefix="", 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) |
SGIO * | get_global_io () |
void | set_global_parallel (Parallel *parallel) |
Parallel * | get_global_parallel () |
void | set_global_version (Version *version) |
Version * | get_global_version () |
SGStringList< char > | get_modelsel_names () |
void | print_modsel_params () |
char * | get_modsel_param_descr (const char *param_name) |
index_t | get_modsel_param_index (const char *param_name) |
void | build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict) |
virtual void | update_parameter_hash () |
virtual bool | parameter_hash_changed () |
virtual bool | equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false) |
virtual CSGObject * | clone () |
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 void | precompute () |
virtual CFeatures * | create_transformed_copy (CFeatures *features, index_t idx) |
virtual CFeatures * | apply_backward_elimination (CFeatures *features) |
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) |
Default constructor
Definition at line 37 of file KernelDependenceMaximization.cpp.
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Destructor
Definition at line 54 of file KernelDependenceMaximization.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 |
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.
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 |
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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 1244 of file SGObject.cpp.
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performs cleanup
Implements CPreprocessor.
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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 1361 of file SGObject.cpp.
Method that computes the measures using test statistic computed by an instance of CIndependenceTest wiht the provided features and the labels
features | the features on which the measure has to be computed |
idx | the index that decides which features should we compute the measure on |
Implements CFeatureSelection< float64_t >.
Definition at line 106 of file DependenceMaximization.cpp.
Helper method which removes the dimension specified via the index. It copies the rest of the features into a separate object via copy_dimension_subset() call.
features | the features |
idx | index of the dimension which is required to be removed |
Definition at line 78 of file DependenceMaximization.cpp.
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A deep copy. All the instance variables will also be copied.
Definition at line 200 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 1265 of file SGObject.cpp.
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Implements CPreprocessor.
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Implements CPreprocessor.
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CKernel * get_kernel_features | ( | ) | const |
Definition at line 131 of file KernelDependenceMaximization.cpp.
CKernel * get_kernel_labels | ( | ) | const |
Definition at line 137 of file KernelDependenceMaximization.cpp.
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Definition at line 1136 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 1160 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 1173 of file SGObject.cpp.
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Reimplemented from CDependenceMaximization.
Reimplemented in CBAHSIC.
Definition at line 79 of file KernelDependenceMaximization.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 |
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Initialize preprocessor from features
features | the features |
Implements CPreprocessor.
Definition at line 63 of file DependenceMaximization.cpp.
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If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.
generic | set to the type of the generic if returning TRUE |
Definition at line 298 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 705 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 546 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 375 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 occurs. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 1063 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 occurs. |
Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 1058 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 743 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 950 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 890 of file SGObject.cpp.
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Definition at line 264 of file SGObject.cpp.
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Precomputes the kernel on labels and replaces the m_kernel_labels with an instance of CCustomKernel. Labels features are set via CDependenceMaximization::set_labels call.
Reimplemented from CFeatureSelection< float64_t >.
Definition at line 60 of file KernelDependenceMaximization.cpp.
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prints all parameter registered for model selection and their type
Definition at line 1112 of file SGObject.cpp.
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prints registered parameters out
prefix | prefix for members |
Definition at line 310 of file SGObject.cpp.
Method which handles the removal of features based on removal policy. see documentation of CFeatureSelection. For dependence maximization approach, the highest scoring features are removed. Therefore, only m_policy can only be shogun::N_LARGEST, shogun::PERCENTILE_LARGEST. See set_policy() method for specifying the exact policy
features | the features object from which specific features has to be removed |
ranks | the ranks of the features based on their measures, 0 being the lowest rank which corresponds to smallest measure. |
Implements CFeatureSelection< float64_t >.
Definition at line 130 of file DependenceMaximization.cpp.
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Save this object to file.
file | where to save the object; will be closed during returning if PREFIX is an empty string. |
prefix | prefix for members |
param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
Definition at line 316 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 occurs. |
Reimplemented in CKernel.
Definition at line 1073 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::SAVE_SERIALIZABLE_PRE is called.
ShogunException | will 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 1068 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 |
Implements CDependenceMaximization.
Implemented in CBAHSIC.
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Definition at line 42 of file SGObject.cpp.
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Definition at line 47 of file SGObject.cpp.
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Definition at line 52 of file SGObject.cpp.
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Definition at line 57 of file SGObject.cpp.
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Definition at line 62 of file SGObject.cpp.
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Definition at line 67 of file SGObject.cpp.
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Definition at line 72 of file SGObject.cpp.
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Definition at line 77 of file SGObject.cpp.
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Definition at line 82 of file SGObject.cpp.
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Definition at line 87 of file SGObject.cpp.
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Definition at line 92 of file SGObject.cpp.
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Definition at line 97 of file SGObject.cpp.
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Definition at line 102 of file SGObject.cpp.
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Definition at line 107 of file SGObject.cpp.
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Definition at line 112 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 243 of file SGObject.cpp.
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set the version object
version | version object to use |
Definition at line 285 of file SGObject.cpp.
void set_kernel_features | ( | CKernel * | kernel | ) |
kernel | the kernel for features (data) |
Definition at line 99 of file KernelDependenceMaximization.cpp.
void set_kernel_labels | ( | CKernel * | kernel | ) |
kernel | the kernel for labels |
Definition at line 115 of file KernelDependenceMaximization.cpp.
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Setter for labels. This method is overridden to internally convert the labels to a dense feature object and set this feature in the independence test estimator. These labels serve as samples \(\mathbf{Y}\sim q\) in the independence test
labels | the labels |
Reimplemented from CFeatureSelection< float64_t >.
Definition at line 187 of file DependenceMaximization.cpp.
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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 |
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policy | feature removal policy |
Implements CFeatureSelection< float64_t >.
Definition at line 179 of file DependenceMaximization.cpp.
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target_dim | the target dimension to achieve |
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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 194 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 305 of file SGObject.cpp.
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Updates the hash of current parameter combination
Definition at line 250 of file SGObject.cpp.
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io
Definition at line 496 of file SGObject.h.
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Wrapper algorithm for feature selection
Definition at line 302 of file FeatureSelection.h.
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The estimator for performing statistical tests for independence which is used for computing measures
Definition at line 157 of file DependenceMaximization.h.
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parameters wrt which we can compute gradients
Definition at line 511 of file SGObject.h.
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Hash of parameter values
Definition at line 517 of file SGObject.h.
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The kernel for data (features) to be used in CKernelIndependenceTest
Definition at line 93 of file KernelDependenceMaximization.h.
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The kernel for labels to be used in CKernelIndependenceTest
Definition at line 96 of file KernelDependenceMaximization.h.
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The labels for the feature vectors
Definition at line 316 of file FeatureSelection.h.
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The feature for the labels
Definition at line 160 of file DependenceMaximization.h.
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model selection parameters
Definition at line 508 of file SGObject.h.
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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.
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map for different parameter versions
Definition at line 514 of file SGObject.h.
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parameters
Definition at line 505 of file SGObject.h.
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Feature removal policy
Definition at line 305 of file FeatureSelection.h.
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The indices of features that are selected
Definition at line 319 of file FeatureSelection.h.
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Target dimension
Definition at line 299 of file FeatureSelection.h.
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parallel
Definition at line 499 of file SGObject.h.
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version
Definition at line 502 of file SGObject.h.