class SubGradientSVM
Definition at line 23 of file SubGradientSVM.h.
CSubGradientSVM | ( | ) |
default constructor
Definition at line 27 of file SubGradientSVM.cpp.
CSubGradientSVM | ( | float64_t | C, | |
CDotFeatures * | traindat, | |||
CLabels * | trainlab | |||
) |
constructor
C | constant C | |
traindat | training features | |
trainlab | labels for training features |
Definition at line 33 of file SubGradientSVM.cpp.
~CSubGradientSVM | ( | ) | [virtual] |
Definition at line 43 of file SubGradientSVM.cpp.
apply machine to data if data is not specified apply to the current features
data | (test)data to be classified |
Definition at line 162 of file Machine.cpp.
CBinaryLabels * apply_binary | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply linear machine to data for binary classification problem
data | (test)data to be classified |
Reimplemented from CMachine.
Reimplemented in CDomainAdaptationSVMLinear.
Definition at line 57 of file LinearMachine.cpp.
apply get outputs
data | features to compute outputs |
Reimplemented in CFeatureBlockLogisticRegression, and CMultitaskLinearMachine.
Definition at line 63 of file LinearMachine.cpp.
CLatentLabels * apply_latent | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply machine to data in means of latent problem
Reimplemented in CLinearLatentMachine.
Definition at line 242 of file Machine.cpp.
Applies a locked machine on a set of indices. Error if machine is not locked
indices | index vector (of locked features) that is predicted |
Definition at line 197 of file Machine.cpp.
CBinaryLabels * apply_locked_binary | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for binary problems
Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.
Definition at line 248 of file Machine.cpp.
CLatentLabels * apply_locked_latent | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for latent problems
Definition at line 276 of file Machine.cpp.
CMulticlassLabels * apply_locked_multiclass | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for multiclass problems
Definition at line 262 of file Machine.cpp.
CRegressionLabels * apply_locked_regression | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for regression problems
Reimplemented in CKernelMachine.
Definition at line 255 of file Machine.cpp.
CStructuredLabels * apply_locked_structured | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for structured problems
Definition at line 269 of file Machine.cpp.
CMulticlassLabels * apply_multiclass | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply machine to data in means of multiclass classification problem
Reimplemented in CDistanceMachine, CMulticlassMachine, CConjugateIndex, CGaussianNaiveBayes, CKNN, CQDA, CConditionalProbabilityTree, CRelaxedTree, and CVwConditionalProbabilityTree.
Definition at line 230 of file Machine.cpp.
float64_t apply_one | ( | int32_t | vec_idx | ) | [virtual, inherited] |
applies to one vector
Reimplemented from CMachine.
Reimplemented in CFeatureBlockLogisticRegression, CMultitaskLeastSquaresRegression, CMultitaskLinearMachine, and CMultitaskLogisticRegression.
Definition at line 46 of file LinearMachine.cpp.
CRegressionLabels * apply_regression | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply linear machine to data for regression problem
data | (test)data to be classified |
Reimplemented from CMachine.
Definition at line 51 of file LinearMachine.cpp.
CStructuredLabels * apply_structured | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply machine to data in means of SO classification problem
Reimplemented in CLinearStructuredOutputMachine.
Definition at line 236 of file Machine.cpp.
void build_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.
dict | dictionary of parameters to be built. |
Definition at line 1201 of file SGObject.cpp.
void cleanup | ( | ) | [protected] |
de-alloc helper arrays
Definition at line 492 of file SubGradientSVM.cpp.
virtual CMachine* clone | ( | ) | [virtual, inherited] |
float64_t compute_min_subgradient | ( | int32_t | num_feat, | |
int32_t | num_vec, | |||
int32_t | num_active, | |||
int32_t | num_bound | |||
) | [protected] |
compute minimum norm subgradient return norm of minimum norm subgradient
Definition at line 289 of file SubGradientSVM.cpp.
float64_t compute_objective | ( | int32_t | num_feat, | |
int32_t | num_vec | |||
) | [protected] |
compute svm objective
Definition at line 393 of file SubGradientSVM.cpp.
void compute_projection | ( | int32_t | num_feat, | |
int32_t | num_vec | |||
) | [protected] |
compute projection
Definition at line 406 of file SubGradientSVM.cpp.
Locks the machine on given labels and data. After this call, only train_locked and apply_locked may be called
Only possible if supports_locking() returns true
labs | labels used for locking | |
features | features used for locking |
Reimplemented in CKernelMachine.
Definition at line 122 of file Machine.cpp.
void data_unlock | ( | ) | [virtual, inherited] |
Unlocks a locked machine and restores previous state
Reimplemented in CKernelMachine.
Definition at line 153 of file Machine.cpp.
virtual CSGObject* deep_copy | ( | ) | const [virtual, inherited] |
A deep copy. All the instance variables will also be copied.
Definition at line 131 of file SGObject.h.
int32_t find_active | ( | int32_t | num_feat, | |
int32_t | num_vec, | |||
int32_t & | num_active, | |||
int32_t & | num_bound | |||
) | [protected] |
returns number of changed constraints for precision work_epsilon and fills active array
Definition at line 80 of file SubGradientSVM.cpp.
virtual float64_t get_bias | ( | ) | [virtual, inherited] |
get bias
Reimplemented in CMultitaskLinearMachine.
Definition at line 104 of file LinearMachine.h.
bool get_bias_enabled | ( | ) |
float64_t get_C1 | ( | ) |
float64_t get_C2 | ( | ) |
virtual EMachineType get_classifier_type | ( | ) | [virtual] |
get classifier type
Reimplemented from CMachine.
Definition at line 48 of file SubGradientSVM.h.
float64_t get_epsilon | ( | ) |
virtual CDotFeatures* get_features | ( | ) | [virtual, inherited] |
SGIO * get_global_io | ( | ) | [inherited] |
Parallel * get_global_parallel | ( | ) | [inherited] |
Version * get_global_version | ( | ) | [inherited] |
CLabels * get_labels | ( | ) | [virtual, inherited] |
virtual EProblemType get_machine_problem_type | ( | ) | const [virtual, inherited] |
returns type of problem machine solves
Reimplemented in CBaseMulticlassMachine.
float64_t get_max_train_time | ( | ) | [inherited] |
SGStringList< char > get_modelsel_names | ( | ) | [inherited] |
Definition at line 1108 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
param_name | name of the parameter |
Definition at line 1132 of file SGObject.cpp.
index_t get_modsel_param_index | ( | const char * | param_name | ) | [inherited] |
Returns index of model selection parameter with provided index
param_name | name of model selection parameter |
Definition at line 1145 of file SGObject.cpp.
virtual const char* get_name | ( | ) | const [protected, virtual] |
Reimplemented from CLinearMachine.
Definition at line 154 of file SubGradientSVM.h.
int32_t get_qpsize | ( | ) |
int32_t get_qpsize_max | ( | ) |
ESolverType get_solver_type | ( | ) | [inherited] |
get w
Reimplemented in CMultitaskLinearMachine.
Definition at line 77 of file LinearMachine.h.
void init | ( | int32_t | num_vec, | |
int32_t | num_feat | |||
) | [protected] |
alloc helper arrays
Definition at line 417 of file SubGradientSVM.cpp.
bool is_data_locked | ( | ) | const [inherited] |
bool is_generic | ( | EPrimitiveType * | generic | ) | const [virtual, inherited] |
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.
virtual bool is_label_valid | ( | CLabels * | lab | ) | const [protected, virtual, inherited] |
check whether the labels is valid.
Subclasses can override this to implement their check of label types.
lab | the labels being checked, guaranteed to be non-NULL |
Reimplemented in CBaseMulticlassMachine.
float64_t line_search | ( | int32_t | num_feat, | |
int32_t | num_vec | |||
) | [protected] |
performs a line search to determine step size
Definition at line 223 of file SubGradientSVM.cpp.
DynArray< TParameter * > * load_all_file_parameters | ( | int32_t | file_version, | |
int32_t | current_version, | |||
CSerializableFile * | file, | |||
const char * | prefix = "" | |||
) | [inherited] |
maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)
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.
DynArray< TParameter * > * load_file_parameters | ( | const SGParamInfo * | param_info, | |
int32_t | file_version, | |||
CSerializableFile * | file, | |||
const char * | prefix = "" | |||
) | [inherited] |
loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned
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.
bool load_serializable | ( | CSerializableFile * | file, | |
const char * | prefix = "" , |
|||
int32_t | param_version = VERSION_PARAMETER | |||
) | [virtual, inherited] |
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.
void load_serializable_post | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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 CLinearHMM, CAlphabet, CANOVAKernel, CCircularKernel, CExponentialKernel, CGaussianKernel, CInverseMultiQuadricKernel, CKernel, CWeightedDegreePositionStringKernel, and CList.
Definition at line 1033 of file SGObject.cpp.
void load_serializable_pre | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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.
MACHINE_PROBLEM_TYPE | ( | PT_BINARY | ) |
problem type
void map_parameters | ( | DynArray< TParameter * > * | param_base, | |
int32_t & | base_version, | |||
DynArray< const SGParamInfo * > * | target_param_infos | |||
) | [inherited] |
Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match
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.
TParameter * migrate | ( | DynArray< TParameter * > * | param_base, | |
const SGParamInfo * | target | |||
) | [protected, virtual, inherited] |
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.
void one_to_one_migration_prepare | ( | DynArray< TParameter * > * | param_base, | |
const SGParamInfo * | target, | |||
TParameter *& | replacement, | |||
TParameter *& | to_migrate, | |||
char * | old_name = NULL | |||
) | [protected, virtual, inherited] |
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.
post lock
Reimplemented in CMultitaskCompositeMachine, and CMultitaskLinearMachine.
void print_modsel_params | ( | ) | [inherited] |
prints all parameter registered for model selection and their type
Definition at line 1084 of file SGObject.cpp.
void print_serializable | ( | const char * | prefix = "" |
) | [virtual, inherited] |
prints registered parameters out
prefix | prefix for members |
Definition at line 290 of file SGObject.cpp.
bool save_serializable | ( | CSerializableFile * | file, | |
const char * | prefix = "" , |
|||
int32_t | param_version = VERSION_PARAMETER | |||
) | [virtual, inherited] |
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.
void save_serializable_post | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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.
void save_serializable_pre | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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.
virtual void set_bias | ( | float64_t | b | ) | [virtual, inherited] |
set bias
b | new bias |
Reimplemented in CMultitaskLinearMachine.
Definition at line 95 of file LinearMachine.h.
void set_bias_enabled | ( | bool | enable_bias | ) |
set if bias shall be enabled
enable_bias | if bias shall be enabled |
Definition at line 74 of file SubGradientSVM.h.
void set_epsilon | ( | float64_t | eps | ) |
virtual void set_features | ( | CDotFeatures * | feat | ) | [virtual, inherited] |
set features
feat | features to set |
Reimplemented in CLDA, CLPBoost, and CLPM.
Definition at line 113 of file LinearMachine.h.
void set_generic< floatmax_t > | ( | ) | [inherited] |
set generic type to T
void set_global_io | ( | SGIO * | io | ) | [inherited] |
void set_global_parallel | ( | Parallel * | parallel | ) | [inherited] |
set the parallel object
parallel | parallel object to use |
Definition at line 230 of file SGObject.cpp.
void set_global_version | ( | Version * | version | ) | [inherited] |
set the version object
version | version object to use |
Definition at line 265 of file SGObject.cpp.
void set_labels | ( | CLabels * | lab | ) | [virtual, inherited] |
set labels
lab | labels |
Reimplemented in CMulticlassMachine, and CRelaxedTree.
Definition at line 75 of file Machine.cpp.
void set_max_train_time | ( | float64_t | t | ) | [inherited] |
set maximum training time
t | maximimum training time |
Definition at line 92 of file Machine.cpp.
void set_qpsize | ( | int32_t | q | ) |
void set_qpsize_max | ( | int32_t | q | ) |
void set_solver_type | ( | ESolverType | st | ) | [inherited] |
void set_store_model_features | ( | bool | store_model | ) | [virtual, inherited] |
Setter for store-model-features-after-training flag
store_model | whether model should be stored after training |
Definition at line 117 of file Machine.cpp.
set w
src_w | new w |
Reimplemented in CMultitaskLinearMachine.
Definition at line 86 of file LinearMachine.h.
virtual CSGObject* shallow_copy | ( | ) | const [virtual, inherited] |
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.
virtual void store_model_features | ( | ) | [protected, virtual, inherited] |
Stores feature data of underlying model. Does nothing because Linear machines store the normal vector of the separating hyperplane and therefore the model anyway
Reimplemented from CMachine.
Definition at line 171 of file LinearMachine.h.
virtual bool supports_locking | ( | ) | const [virtual, inherited] |
Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.
bool train | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
train machine
data | training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data). If flag is set, model features will be stored after training. |
Reimplemented in COnlineSVMSGD, CSGDQN, and CRelaxedTree.
Definition at line 49 of file Machine.cpp.
Trains a locked machine on a set of indices. Error if machine is not locked
NOT IMPLEMENTED
indices | index vector (of locked features) that is used for training |
Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.
bool train_machine | ( | CFeatures * | data = NULL |
) | [protected, virtual] |
train SVM classifier
data | training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data) |
Reimplemented from CMachine.
Definition at line 529 of file SubGradientSVM.cpp.
virtual bool train_require_labels | ( | ) | const [protected, virtual, inherited] |
returns whether machine require labels for training
Reimplemented in CLibSVMOneClass, CHierarchical, CKMeans, CLinearLatentMachine, COnlineLinearMachine, CConditionalProbabilityTree, and CVwConditionalProbabilityTree.
void unset_generic | ( | ) | [inherited] |
unset generic type
this has to be called in classes specializing a template class
Definition at line 285 of file SGObject.cpp.
void update_active | ( | int32_t | num_feat, | |
int32_t | num_vec | |||
) | [protected] |
swaps the active / old_active and computes idx_active, idx_bound and sum_CXy_active arrays and the sum_Cy_active variable
Definition at line 202 of file SubGradientSVM.cpp.
bool update_parameter_hash | ( | ) | [protected, virtual, inherited] |
Updates the hash of current parameter combination.
Definition at line 237 of file SGObject.cpp.
void update_projection | ( | float64_t | alpha, | |
int32_t | num_vec | |||
) | [protected] |
only computes updates on the projection
Definition at line 412 of file SubGradientSVM.cpp.
uint8_t* active [protected] |
0=not active, 1=active, 2=on boundary
Definition at line 194 of file SubGradientSVM.h.
float64_t autoselected_epsilon [protected] |
autoselected epsilon
Definition at line 177 of file SubGradientSVM.h.
beta
Definition at line 236 of file SubGradientSVM.h.
bias
Definition at line 181 of file LinearMachine.h.
C1
Definition at line 169 of file SubGradientSVM.h.
C2
Definition at line 171 of file SubGradientSVM.h.
int32_t delta_active [protected] |
delta active
Definition at line 202 of file SubGradientSVM.h.
int32_t delta_bound [protected] |
delta bound
Definition at line 204 of file SubGradientSVM.h.
epsilon
Definition at line 173 of file SubGradientSVM.h.
CDotFeatures* features [protected, inherited] |
features
Definition at line 183 of file LinearMachine.h.
grad b
Definition at line 226 of file SubGradientSVM.h.
grad proj
Definition at line 228 of file SubGradientSVM.h.
grad w
Definition at line 224 of file SubGradientSVM.h.
int32_t* hinge_idx [protected] |
hinge index
Definition at line 232 of file SubGradientSVM.h.
float64_t* hinge_point [protected] |
hinge point
Definition at line 230 of file SubGradientSVM.h.
int32_t* idx_active [protected] |
idx active
Definition at line 198 of file SubGradientSVM.h.
int32_t* idx_bound [protected] |
idx bound
Definition at line 200 of file SubGradientSVM.h.
io
Definition at line 462 of file SGObject.h.
int32_t last_it_noimprovement [protected] |
last iteration no improvement
Definition at line 188 of file SubGradientSVM.h.
bool m_data_locked [protected, inherited] |
uint32_t m_hash [inherited] |
Hash of parameter values
Definition at line 480 of file SGObject.h.
float64_t m_max_train_time [protected, inherited] |
Parameter* m_model_selection_parameters [inherited] |
model selection parameters
Definition at line 474 of file SGObject.h.
ParameterMap* m_parameter_map [inherited] |
map for different parameter versions
Definition at line 477 of file SGObject.h.
Parameter* m_parameters [inherited] |
parameters
Definition at line 471 of file SGObject.h.
ESolverType m_solver_type [protected, inherited] |
bool m_store_model_features [protected, inherited] |
int32_t num_it_noimprovement [protected] |
number of iterations no improvement
Definition at line 190 of file SubGradientSVM.h.
uint8_t* old_active [protected] |
old active
Definition at line 196 of file SubGradientSVM.h.
old beta
Definition at line 238 of file SubGradientSVM.h.
old v
Definition at line 218 of file SubGradientSVM.h.
old Z
Definition at line 246 of file SubGradientSVM.h.
old Zv
Definition at line 242 of file SubGradientSVM.h.
parallel
Definition at line 465 of file SGObject.h.
proj
Definition at line 206 of file SubGradientSVM.h.
int32_t qpsize [protected] |
qpsize
Definition at line 179 of file SubGradientSVM.h.
int32_t qpsize_limit [protected] |
limit of qpsize
Definition at line 183 of file SubGradientSVM.h.
int32_t qpsize_max [protected] |
maximum qpsize
Definition at line 181 of file SubGradientSVM.h.
float64_t* sum_CXy_active [protected] |
sum CXy active
Definition at line 214 of file SubGradientSVM.h.
float64_t sum_Cy_active [protected] |
sum Cy active
Definition at line 220 of file SubGradientSVM.h.
timing measurement
Definition at line 249 of file SubGradientSVM.h.
tmp proj
Definition at line 208 of file SubGradientSVM.h.
int32_t* tmp_proj_idx [protected] |
tmp proj index
Definition at line 210 of file SubGradientSVM.h.
bool use_bias [protected] |
shall bias be used
Definition at line 185 of file SubGradientSVM.h.
v
Definition at line 216 of file SubGradientSVM.h.
version
Definition at line 468 of file SGObject.h.
w
Definition at line 179 of file LinearMachine.h.
float64_t work_epsilon [protected] |
work epsilon
Definition at line 175 of file SubGradientSVM.h.
Z
Definition at line 244 of file SubGradientSVM.h.
Zv
Definition at line 240 of file SubGradientSVM.h.