SHOGUN
v2.0.0
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UI classifier.
Definition at line 24 of file GUIClassifier.h.
Public Member Functions | |
CGUIClassifier () | |
CGUIClassifier (CSGInterface *interface) | |
~CGUIClassifier () | |
bool | new_classifier (char *name, int32_t d=6, int32_t from_d=40) |
bool | set_max_train_time (float64_t max) |
bool | load (char *filename, char *type) |
bool | save (char *param) |
CLabels * | classify () |
CLabels * | classify_kernelmachine () |
CLabels * | classify_distancemachine () |
CLabels * | classify_linear () |
CLabels * | classify_byte_linear () |
bool | classify_example (int32_t idx, float64_t &result) |
CMachine * | get_classifier () |
bool | get_trained_classifier (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols, int32_t idx=-1) |
int32_t | get_num_svms () |
bool | get_svm (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols, int32_t idx=-1) |
bool | get_linear (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols) |
bool | get_clustering (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols) |
bool | set_perceptron_parameters (float64_t lernrate, int32_t maxiter) |
bool | set_svm_C (float64_t C1, float64_t C2) |
bool | set_svm_bufsize (int32_t bufsize) |
bool | set_svm_qpsize (int32_t qpsize) |
bool | set_svm_max_qpsize (int32_t max_qpsize) |
bool | set_svm_shrinking_enabled (bool enabled) |
bool | set_svm_nu (float64_t nu) |
bool | set_svm_batch_computation_enabled (bool enabled) |
bool | set_do_auc_maximization (bool do_auc) |
bool | set_svm_linadd_enabled (bool enabled) |
bool | set_svm_bias_enabled (bool enabled) |
bool | set_mkl_interleaved_enabled (bool enabled) |
bool | set_svm_epsilon (float64_t epsilon) |
bool | set_svr_tube_epsilon (float64_t tube_epsilon) |
bool | set_svm_mkl_parameters (float64_t weight_epsilon, float64_t C_mkl, float64_t mkl_norm) |
bool | set_mkl_block_norm (float64_t mkl_bnorm) |
bool | set_elasticnet_lambda (float64_t lambda) |
bool | set_svm_precompute_enabled (int32_t precompute) |
bool | set_krr_tau (float64_t tau=1) |
bool | set_solver (char *solver) |
bool | set_constraint_generator (char *cg) |
bool | train_mkl_multiclass () |
bool | train_mkl () |
bool | train_svm () |
bool | train_knn (int32_t k=3) |
bool | train_krr () |
bool | train_clustering (int32_t k=3, int32_t max_iter=1000) |
bool | train_linear (float64_t gamma=0) |
bool | train_sparse_linear () |
bool | train_wdocas () |
virtual const char * | get_name () const |
virtual CSGObject * | shallow_copy () const |
virtual CSGObject * | deep_copy () const |
virtual bool | is_generic (EPrimitiveType *generic) const |
template<class T > | |
void | set_generic () |
void | unset_generic () |
virtual void | print_serializable (const char *prefix="") |
virtual bool | save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=VERSION_PARAMETER) |
virtual bool | load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=VERSION_PARAMETER) |
DynArray< TParameter * > * | load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="") |
DynArray< TParameter * > * | load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="") |
void | map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos) |
void | set_global_io (SGIO *io) |
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_parameter_dictionary (CMap< TParameter *, CSGObject * > &dict) |
Public Attributes | |
SGIO * | io |
Parallel * | parallel |
Version * | version |
Parameter * | m_parameters |
Parameter * | m_model_selection_parameters |
ParameterMap * | m_parameter_map |
uint32_t | m_hash |
Protected Member Functions | |
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) |
virtual bool | update_parameter_hash () |
Protected Attributes | |
CSGInterface * | ui |
CMachine * | classifier |
float64_t | max_train_time |
float64_t | perceptron_learnrate |
int32_t | perceptron_maxiter |
int32_t | svm_qpsize |
int32_t | svm_bufsize |
int32_t | svm_max_qpsize |
float64_t | mkl_norm |
float64_t | mkl_block_norm |
float64_t | ent_lambda |
float64_t | svm_weight_epsilon |
float64_t | svm_epsilon |
float64_t | svm_tube_epsilon |
float64_t | svm_nu |
float64_t | svm_C1 |
float64_t | svm_C2 |
float64_t | C_mkl |
float64_t | krr_tau |
bool | mkl_use_interleaved |
bool | svm_use_bias |
bool | svm_use_batch_computation |
bool | svm_use_linadd |
bool | svm_use_precompute |
bool | svm_use_precompute_subkernel |
bool | svm_use_precompute_subkernel_light |
bool | svm_use_shrinking |
bool | svm_do_auc_maximization |
CSVM * | constraint_generator |
ESolverType | solver_type |
CGUIClassifier | ( | ) |
constructor
Definition at line 28 of file GUIClassifier.h.
CGUIClassifier | ( | CSGInterface * | interface | ) |
~CGUIClassifier | ( | ) |
destructor
Definition at line 110 of file GUIClassifier.cpp.
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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.
dict | dictionary of parameters to be built. |
Definition at line 1204 of file SGObject.cpp.
CLabels * classify | ( | ) |
classify
Definition at line 1123 of file GUIClassifier.cpp.
CLabels * classify_byte_linear | ( | ) |
classify byte linear
Definition at line 1460 of file GUIClassifier.cpp.
CLabels * classify_distancemachine | ( | ) |
classify distance machine
Definition at line 1398 of file GUIClassifier.cpp.
bool classify_example | ( | int32_t | idx, |
float64_t & | result | ||
) |
CLabels * classify_kernelmachine | ( | ) |
classify kernel machine
Definition at line 1173 of file GUIClassifier.cpp.
CLabels * classify_linear | ( | ) |
classify linear
Definition at line 1435 of file GUIClassifier.cpp.
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virtualinherited |
A deep copy. All the instance variables will also be copied.
Definition at line 131 of file SGObject.h.
CMachine* get_classifier | ( | ) |
get classifier
Definition at line 62 of file GUIClassifier.h.
bool get_clustering | ( | float64_t *& | weights, |
int32_t & | rows, | ||
int32_t & | cols, | ||
float64_t *& | bias, | ||
int32_t & | brows, | ||
int32_t & | bcols | ||
) |
get clustering
weights | |
rows | |
cols | |
bias | |
brows | |
bcols |
Definition at line 1318 of file GUIClassifier.cpp.
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inherited |
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inherited |
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bool get_linear | ( | float64_t *& | weights, |
int32_t & | rows, | ||
int32_t & | cols, | ||
float64_t *& | bias, | ||
int32_t & | brows, | ||
int32_t & | bcols | ||
) |
get linear
weights | |
rows | |
cols | |
bias | |
brows | |
bcols |
Definition at line 1374 of file GUIClassifier.cpp.
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inherited |
Definition at line 1108 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 1132 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 1145 of file SGObject.cpp.
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int32_t get_num_svms | ( | ) |
get number of SVMs in Multiclass
Definition at line 1280 of file GUIClassifier.cpp.
bool get_svm | ( | float64_t *& | weights, |
int32_t & | rows, | ||
int32_t & | cols, | ||
float64_t *& | bias, | ||
int32_t & | brows, | ||
int32_t & | bcols, | ||
int32_t | idx = -1 |
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) |
get svm
weights | |
rows | |
cols | |
bias | |
brows | |
bcols | |
idx |
Definition at line 1286 of file GUIClassifier.cpp.
bool get_trained_classifier | ( | float64_t *& | weights, |
int32_t & | rows, | ||
int32_t & | cols, | ||
float64_t *& | bias, | ||
int32_t & | brows, | ||
int32_t & | bcols, | ||
int32_t | idx = -1 |
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) |
get trained classifier
weights | |
rows | |
cols | |
bias | |
brows | |
bcols | |
idx |
Definition at line 1223 of file GUIClassifier.cpp.
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virtualinherited |
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 278 of file SGObject.cpp.
bool load | ( | char * | filename, |
char * | type | ||
) |
load classifier from file
Definition at line 832 of file GUIClassifier.cpp.
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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)
file_version | parameter version of the file |
current_version | version from which mapping begins (you want to use VERSION_PARAMETER for this in most cases) |
file | file to load from |
prefix | prefix for members |
Definition at line 679 of file SGObject.cpp.
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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
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 523 of file SGObject.cpp.
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virtualinherited |
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) |
Reimplemented in CModelSelectionParameters.
Definition at line 354 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CANOVAKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 1033 of file SGObject.cpp.
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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::LOAD_SERIALIZABLE_PRE is called.
ShogunException | Will be thrown if an error occurres. |
Definition at line 1028 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 717 of file SGObject.cpp.
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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
param_base | set of TParameter instances to use for migration |
target | parameter info for the resulting TParameter |
Definition at line 923 of file SGObject.cpp.
bool new_classifier | ( | char * | name, |
int32_t | d = 6 , |
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int32_t | from_d = 40 |
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create new classifier
Definition at line 116 of file GUIClassifier.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 864 of file SGObject.cpp.
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prints all parameter registered for model selection and their type
Definition at line 1084 of file SGObject.cpp.
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virtualinherited |
prints registered parameters out
prefix | prefix for members |
Definition at line 290 of file SGObject.cpp.
bool save | ( | char * | param | ) |
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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) |
Reimplemented in CModelSelectionParameters.
Definition at line 296 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel.
Definition at line 1043 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.
Definition at line 1038 of file SGObject.cpp.
bool set_constraint_generator | ( | char * | cg | ) |
set constraint generator
Definition at line 1591 of file GUIClassifier.cpp.
bool set_do_auc_maximization | ( | bool | do_auc | ) |
bool set_elasticnet_lambda | ( | float64_t | lambda | ) |
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set generic type to T
Definition at line 41 of file SGObject.cpp.
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set the parallel object
parallel | parallel object to use |
Definition at line 230 of file SGObject.cpp.
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set the version object
version | version object to use |
Definition at line 265 of file SGObject.cpp.
bool set_krr_tau | ( | float64_t | tau = 1 | ) |
set KRR's tau
Definition at line 1527 of file GUIClassifier.cpp.
bool set_max_train_time | ( | float64_t | max | ) |
set maximum train time
Definition at line 919 of file GUIClassifier.cpp.
bool set_mkl_block_norm | ( | float64_t | mkl_bnorm | ) |
bool set_mkl_interleaved_enabled | ( | bool | enabled | ) |
bool set_perceptron_parameters | ( | float64_t | lernrate, |
int32_t | maxiter | ||
) |
set perceptron parameters
lernrate | |
maxiter |
Definition at line 891 of file GUIClassifier.cpp.
bool set_solver | ( | char * | solver | ) |
set solver type
Definition at line 1540 of file GUIClassifier.cpp.
bool set_svm_batch_computation_enabled | ( | bool | enabled | ) |
set svm batch computation enabled
enabled |
Definition at line 1066 of file GUIClassifier.cpp.
bool set_svm_bias_enabled | ( | bool | enabled | ) |
bool set_svm_bufsize | ( | int32_t | bufsize | ) |
bool set_svm_epsilon | ( | float64_t | epsilon | ) |
bool set_svm_linadd_enabled | ( | bool | enabled | ) |
bool set_svm_max_qpsize | ( | int32_t | max_qpsize | ) |
set svm mkl parameters
weight_epsilon | |
C_mkl | |
mkl_norm |
Definition at line 965 of file GUIClassifier.cpp.
bool set_svm_nu | ( | float64_t | nu | ) |
bool set_svm_precompute_enabled | ( | int32_t | precompute | ) |
set svm precompute enabled
precompute |
bool set_svm_qpsize | ( | int32_t | qpsize | ) |
bool set_svm_shrinking_enabled | ( | bool | enabled | ) |
bool set_svr_tube_epsilon | ( | float64_t | tube_epsilon | ) |
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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 122 of file SGObject.h.
bool train_clustering | ( | int32_t | k = 3 , |
int32_t | max_iter = 1000 |
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) |
train clustering
Definition at line 648 of file GUIClassifier.cpp.
bool train_knn | ( | int32_t | k = 3 | ) |
train K-nearest-neighbour
Definition at line 684 of file GUIClassifier.cpp.
bool train_krr | ( | ) |
train kernel ridge regression
Definition at line 711 of file GUIClassifier.cpp.
bool train_linear | ( | float64_t | gamma = 0 | ) |
train linear classifier
gamma | gamma parameter of LDA |
Definition at line 748 of file GUIClassifier.cpp.
bool train_mkl | ( | ) |
train MKL
Definition at line 483 of file GUIClassifier.cpp.
bool train_mkl_multiclass | ( | ) |
train MKL multiclass
Definition at line 437 of file GUIClassifier.cpp.
bool train_sparse_linear | ( | ) |
train sparse linear classifier
bool train_svm | ( | ) |
train SVM
Definition at line 552 of file GUIClassifier.cpp.
bool train_wdocas | ( | ) |
train WD OCAS
Definition at line 808 of file GUIClassifier.cpp.
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unset generic type
this has to be called in classes specializing a template class
Definition at line 285 of file SGObject.cpp.
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Updates the hash of current parameter combination.
Definition at line 237 of file SGObject.cpp.
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C mkl
Definition at line 264 of file GUIClassifier.h.
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classifier
Definition at line 232 of file GUIClassifier.h.
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constraint generator
Definition at line 287 of file GUIClassifier.h.
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ent lambda
Definition at line 250 of file GUIClassifier.h.
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io
Definition at line 462 of file SGObject.h.
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krr tau
Definition at line 266 of file GUIClassifier.h.
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Hash of parameter values
Definition at line 480 of file SGObject.h.
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model selection parameters
Definition at line 474 of file SGObject.h.
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map for different parameter versions
Definition at line 477 of file SGObject.h.
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parameters
Definition at line 471 of file SGObject.h.
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max train time
Definition at line 234 of file GUIClassifier.h.
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mkl block norm
Definition at line 248 of file GUIClassifier.h.
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mkl norm
Definition at line 246 of file GUIClassifier.h.
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mkl use interleaved
Definition at line 268 of file GUIClassifier.h.
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parallel
Definition at line 465 of file SGObject.h.
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perceptron learnrate
Definition at line 236 of file GUIClassifier.h.
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perceptron maxiter
Definition at line 238 of file GUIClassifier.h.
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solver type
Definition at line 289 of file GUIClassifier.h.
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svm bufsize
Definition at line 242 of file GUIClassifier.h.
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svm C1
Definition at line 260 of file GUIClassifier.h.
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svm C2
Definition at line 262 of file GUIClassifier.h.
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svm do auc maximization
Definition at line 284 of file GUIClassifier.h.
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svm epsilon
Definition at line 254 of file GUIClassifier.h.
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svm max qpsize
Definition at line 244 of file GUIClassifier.h.
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svm nu
Definition at line 258 of file GUIClassifier.h.
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svm qpsize
Definition at line 240 of file GUIClassifier.h.
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svm tube epsilon
Definition at line 256 of file GUIClassifier.h.
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svm use batch computation
Definition at line 272 of file GUIClassifier.h.
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svm use bias
Definition at line 270 of file GUIClassifier.h.
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svm use linadd
Definition at line 274 of file GUIClassifier.h.
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svm use precompute
Definition at line 276 of file GUIClassifier.h.
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svm use precompute subkernel
Definition at line 278 of file GUIClassifier.h.
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svm use precompute subkernel light
Definition at line 280 of file GUIClassifier.h.
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svm use shrinking
Definition at line 282 of file GUIClassifier.h.
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svm weight epsilon
Definition at line 252 of file GUIClassifier.h.
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ui
Definition at line 230 of file GUIClassifier.h.
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version
Definition at line 468 of file SGObject.h.