SHOGUN
6.1.3
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class OnlineSVMSGD
Definition at line 35 of file OnlineSVMSGD.h.
Public Types | |
typedef rxcpp::subjects::subject< ObservedValue > | SGSubject |
typedef rxcpp::observable< ObservedValue, rxcpp::dynamic_observable< ObservedValue > > | SGObservable |
typedef rxcpp::subscriber< ObservedValue, rxcpp::observer< ObservedValue, void, void, void, void > > | SGSubscriber |
Public Member Functions | |
MACHINE_PROBLEM_TYPE (PT_BINARY) | |
COnlineSVMSGD () | |
COnlineSVMSGD (float64_t C) | |
COnlineSVMSGD (float64_t C, CStreamingDotFeatures *traindat) | |
virtual | ~COnlineSVMSGD () |
virtual EMachineType | get_classifier_type () |
virtual bool | train (CFeatures *data=NULL) |
void | set_C (float64_t c_neg, float64_t c_pos) |
float64_t | get_C1 () |
float64_t | get_C2 () |
void | set_epochs (int32_t e) |
int32_t | get_epochs () |
void | set_lambda (float64_t l) |
float64_t | get_lambda () |
void | set_bias_enabled (bool enable_bias) |
bool | get_bias_enabled () |
void | set_regularized_bias_enabled (bool enable_bias) |
bool | get_regularized_bias_enabled () |
void | set_loss_function (CLossFunction *loss_func) |
CLossFunction * | get_loss_function () |
const char * | get_name () const |
virtual void | get_w (float64_t *&dst_w, int32_t &dst_dims) |
virtual SGVector< float32_t > | get_w () const |
virtual void | set_w (const SGVector< float32_t > w) |
virtual void | set_w (float64_t *src_w, int32_t src_w_dim) |
virtual void | set_bias (float32_t b) |
virtual float32_t | get_bias () |
virtual void | set_features (CStreamingDotFeatures *feat) |
virtual CRegressionLabels * | apply_regression (CFeatures *data=NULL) |
virtual CBinaryLabels * | apply_binary (CFeatures *data=NULL) |
virtual float64_t | apply_one (int32_t vec_idx) |
get output for example "vec_idx" More... | |
virtual float32_t | apply_one (float32_t *vec, int32_t len) |
virtual float32_t | apply_to_current_example () |
virtual CStreamingDotFeatures * | get_features () |
virtual void | start_train () |
virtual void | stop_train () |
virtual void | train_example (CStreamingDotFeatures *feature, float64_t label) |
virtual CLabels * | apply (CFeatures *data=NULL) |
virtual CMulticlassLabels * | apply_multiclass (CFeatures *data=NULL) |
virtual CStructuredLabels * | apply_structured (CFeatures *data=NULL) |
virtual CLatentLabels * | apply_latent (CFeatures *data=NULL) |
virtual void | set_labels (CLabels *lab) |
virtual CLabels * | get_labels () |
void | set_max_train_time (float64_t t) |
float64_t | get_max_train_time () |
void | set_solver_type (ESolverType st) |
ESolverType | get_solver_type () |
virtual void | set_store_model_features (bool store_model) |
virtual bool | train_locked (SGVector< index_t > indices) |
virtual CLabels * | apply_locked (SGVector< index_t > indices) |
virtual CBinaryLabels * | apply_locked_binary (SGVector< index_t > indices) |
virtual CRegressionLabels * | apply_locked_regression (SGVector< index_t > indices) |
virtual CMulticlassLabels * | apply_locked_multiclass (SGVector< index_t > indices) |
virtual CStructuredLabels * | apply_locked_structured (SGVector< index_t > indices) |
virtual CLatentLabels * | apply_locked_latent (SGVector< index_t > indices) |
virtual void | data_lock (CLabels *labs, CFeatures *features) |
virtual void | post_lock (CLabels *labs, CFeatures *features) |
virtual void | data_unlock () |
virtual bool | supports_locking () const |
bool | is_data_locked () const |
virtual EProblemType | get_machine_problem_type () const |
SG_FORCED_INLINE bool | cancel_computation () const |
SG_FORCED_INLINE void | pause_computation () |
SG_FORCED_INLINE void | resume_computation () |
int32_t | ref () |
int32_t | ref_count () |
int32_t | unref () |
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="") |
virtual bool | load_serializable (CSerializableFile *file, const char *prefix="") |
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) |
bool | has (const std::string &name) const |
template<typename T > | |
bool | has (const Tag< T > &tag) const |
template<typename T , typename U = void> | |
bool | has (const std::string &name) const |
template<typename T > | |
void | set (const Tag< T > &_tag, const T &value) |
template<typename T , typename U = void> | |
void | set (const std::string &name, const T &value) |
template<typename T > | |
T | get (const Tag< T > &_tag) const |
template<typename T , typename U = void> | |
T | get (const std::string &name) const |
SGObservable * | get_parameters_observable () |
void | subscribe_to_parameters (ParameterObserverInterface *obs) |
void | list_observable_parameters () |
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 |
uint32_t | m_hash |
Protected Member Functions | |
void | calibrate (int32_t max_vec_num=1000) |
virtual bool | train_machine (CFeatures *data=NULL) |
SGVector< float64_t > | apply_get_outputs (CFeatures *data) |
virtual bool | train_require_labels () const |
virtual void | store_model_features () |
virtual bool | is_label_valid (CLabels *lab) const |
rxcpp::subscription | connect_to_signal_handler () |
void | reset_computation_variables () |
virtual void | on_next () |
virtual void | on_pause () |
virtual void | on_complete () |
virtual void | load_serializable_pre () throw (ShogunException) |
virtual void | load_serializable_post () throw (ShogunException) |
virtual void | save_serializable_pre () throw (ShogunException) |
virtual void | save_serializable_post () throw (ShogunException) |
template<typename T > | |
void | register_param (Tag< T > &_tag, const T &value) |
template<typename T > | |
void | register_param (const std::string &name, const T &value) |
bool | clone_parameters (CSGObject *other) |
void | observe (const ObservedValue value) |
void | register_observable_param (const std::string &name, const SG_OBS_VALUE_TYPE type, const std::string &description) |
Protected Attributes | |
SGVector< float32_t > | m_w |
float32_t | bias |
CStreamingDotFeatures * | features |
float64_t | m_max_train_time |
CLabels * | m_labels |
ESolverType | m_solver_type |
bool | m_store_model_features |
bool | m_data_locked |
std::atomic< bool > | m_cancel_computation |
std::atomic< bool > | m_pause_computation_flag |
std::condition_variable | m_pause_computation |
std::mutex | m_mutex |
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inherited |
Definition at line 130 of file SGObject.h.
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inherited |
Definition at line 127 of file SGObject.h.
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Definition at line 133 of file SGObject.h.
COnlineSVMSGD | ( | ) |
default constructor
Definition at line 32 of file OnlineSVMSGD.cpp.
COnlineSVMSGD | ( | float64_t | C | ) |
COnlineSVMSGD | ( | float64_t | C, |
CStreamingDotFeatures * | traindat | ||
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constructor
C | constant C |
traindat | training features |
Definition at line 47 of file OnlineSVMSGD.cpp.
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virtual |
Definition at line 57 of file OnlineSVMSGD.cpp.
apply machine to data if data is not specified apply to the current features
data | (test)data to be classified |
Definition at line 159 of file Machine.cpp.
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virtualinherited |
apply linear machine to data for binary classification problems
data | (test)data to be classified |
Reimplemented from CMachine.
Definition at line 35 of file OnlineLinearMachine.cpp.
get real outputs
data | features to compute outputs |
Definition at line 47 of file OnlineLinearMachine.cpp.
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virtualinherited |
apply machine to data in means of latent problem
Reimplemented in CLinearLatentMachine.
Definition at line 239 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 194 of file Machine.cpp.
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applies a locked machine on a set of indices for binary problems
Reimplemented in CKernelMachine.
Definition at line 245 of file Machine.cpp.
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applies a locked machine on a set of indices for latent problems
Definition at line 273 of file Machine.cpp.
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applies a locked machine on a set of indices for multiclass problems
Definition at line 259 of file Machine.cpp.
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applies a locked machine on a set of indices for regression problems
Reimplemented in CKernelMachine.
Definition at line 252 of file Machine.cpp.
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applies a locked machine on a set of indices for structured problems
Definition at line 266 of file Machine.cpp.
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apply machine to data in means of multiclass classification problem
Reimplemented in CNeuralNetwork, CCHAIDTree, CCARTree, CGaussianProcessClassification, CKNN, CMulticlassMachine, CC45ClassifierTree, CID3ClassifierTree, CQDA, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CRelaxedTree, and CBaggingMachine.
Definition at line 227 of file Machine.cpp.
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virtualinherited |
get output for example "vec_idx"
Reimplemented from CMachine.
Definition at line 153 of file OnlineLinearMachine.h.
apply linear machine to one vector
vec | feature vector |
len | length of vector |
Definition at line 77 of file OnlineLinearMachine.cpp.
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apply linear machine to data for regression problems
data | (test)data to be classified |
Reimplemented from CMachine.
Definition at line 41 of file OnlineLinearMachine.cpp.
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apply machine to data in means of SO classification problem
Reimplemented in CLinearStructuredOutputMachine.
Definition at line 233 of file Machine.cpp.
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apply linear machine to vector currently being processed
Definition at line 83 of file OnlineLinearMachine.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 635 of file SGObject.cpp.
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protected |
calibrate
max_vec_num | Maximum number of vectors to calibrate using (optional) if set to -1, tries to calibrate using all vectors |
Definition at line 163 of file OnlineSVMSGD.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.
Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicObjectArray, CAlphabet, and CMKL.
Definition at line 734 of file SGObject.cpp.
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Definition at line 759 of file SGObject.cpp.
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connect the machine instance to the signal handler
Definition at line 280 of file Machine.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 119 of file Machine.cpp.
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Unlocks a locked machine and restores previous state
Reimplemented in CKernelMachine.
Definition at line 150 of file Machine.cpp.
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A deep copy. All the instance variables will also be copied.
Definition at line 232 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 656 of file SGObject.cpp.
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Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.
_tag | name and type information of parameter |
Definition at line 381 of file SGObject.h.
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Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.
name | name of the parameter |
Definition at line 404 of file SGObject.h.
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bool get_bias_enabled | ( | ) |
float64_t get_C1 | ( | ) |
float64_t get_C2 | ( | ) |
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get classifier type
Reimplemented from CMachine.
Definition at line 63 of file OnlineSVMSGD.h.
int32_t get_epochs | ( | ) |
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float64_t get_lambda | ( | ) |
get lambda
Definition at line 117 of file OnlineSVMSGD.h.
CLossFunction* get_loss_function | ( | ) |
Return the loss function
Definition at line 153 of file OnlineSVMSGD.h.
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returns type of problem machine solves
Reimplemented in CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree, and CBaseMulticlassMachine.
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Definition at line 536 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 560 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 573 of file SGObject.cpp.
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virtual |
Reimplemented from COnlineLinearMachine.
Definition at line 156 of file OnlineSVMSGD.h.
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bool get_regularized_bias_enabled | ( | ) |
check if regularized bias is enabled
Definition at line 141 of file OnlineSVMSGD.h.
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virtualinherited |
Get w as a _new_ float64_t array
dst_w | store w in this argument |
dst_dims | dimension of w |
Definition at line 66 of file OnlineLinearMachine.h.
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Checks if object has a class parameter identified by a name.
name | name of the parameter |
Definition at line 304 of file SGObject.h.
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inherited |
Checks if object has a class parameter identified by a Tag.
tag | tag of the parameter containing name and type information |
Definition at line 315 of file SGObject.h.
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inherited |
Checks if a type exists for a class parameter identified by a name.
name | name of the parameter |
Definition at line 326 of file SGObject.h.
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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 330 of file SGObject.cpp.
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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 CNeuralNetwork, CCARTree, CCHAIDTree, CGaussianProcessRegression, and CBaseMulticlassMachine.
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Print to stdout a list of observable parameters
Definition at line 878 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 |
Definition at line 403 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 460 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 455 of file SGObject.cpp.
MACHINE_PROBLEM_TYPE | ( | PT_BINARY | ) |
returns type of problem machine solves
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Observe a parameter value and emit them to observer.
value | Observed parameter's value |
Definition at line 828 of file SGObject.cpp.
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protectedvirtualinherited |
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virtualinherited |
Definition at line 296 of file SGObject.cpp.
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prints all parameter registered for model selection and their type
Definition at line 512 of file SGObject.cpp.
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virtualinherited |
prints registered parameters out
prefix | prefix for members |
Definition at line 342 of file SGObject.cpp.
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protectedinherited |
Register which params this object can emit.
name | the param name |
type | the param type |
description | a user oriented description |
Definition at line 871 of file SGObject.cpp.
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protectedinherited |
Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.
_tag | name and type information of parameter |
value | value of the parameter |
Definition at line 472 of file SGObject.h.
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protectedinherited |
Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.
name | name of the parameter |
value | value of the parameter along with type information |
Definition at line 485 of file SGObject.h.
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inherited |
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virtualinherited |
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 |
Definition at line 348 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 occurs. |
Reimplemented in CKernel.
Definition at line 470 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 occurs. |
Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 465 of file SGObject.cpp.
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Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.
_tag | name and type information of parameter |
value | value of the parameter |
Definition at line 342 of file SGObject.h.
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Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.
name | name of the parameter |
value | value of the parameter along with type information |
Definition at line 368 of file SGObject.h.
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void set_bias_enabled | ( | bool | enable_bias | ) |
set if bias shall be enabled
enable_bias | if bias shall be enabled |
Definition at line 123 of file OnlineSVMSGD.h.
set C
c_neg | new C constant for negatively labeled examples |
c_pos | new C constant for positively labeled examples |
Definition at line 81 of file OnlineSVMSGD.h.
void set_epochs | ( | int32_t | e | ) |
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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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Definition at line 113 of file SGObject.cpp.
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Definition at line 118 of file SGObject.cpp.
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Definition at line 123 of file SGObject.cpp.
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Definition at line 128 of file SGObject.cpp.
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Definition at line 133 of file SGObject.cpp.
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Definition at line 138 of file SGObject.cpp.
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Definition at line 143 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 275 of file SGObject.cpp.
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set the version object
version | version object to use |
Definition at line 317 of file SGObject.cpp.
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set labels
lab | labels |
Reimplemented in CNeuralNetwork, CGaussianProcessMachine, CCARTree, CStructuredOutputMachine, CRelaxedTree, and CMulticlassMachine.
Definition at line 72 of file Machine.cpp.
void set_lambda | ( | float64_t | l | ) |
set lambda
l | value of regularization parameter lambda |
Definition at line 111 of file OnlineSVMSGD.h.
void set_loss_function | ( | CLossFunction * | loss_func | ) |
Set the loss function to use
loss_func | object derived from CLossFunction |
Definition at line 62 of file OnlineSVMSGD.cpp.
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inherited |
set maximum training time
t | maximimum training time |
Definition at line 89 of file Machine.cpp.
void set_regularized_bias_enabled | ( | bool | enable_bias | ) |
set if regularized bias shall be enabled
enable_bias | if regularized bias shall be enabled |
Definition at line 135 of file OnlineSVMSGD.h.
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virtualinherited |
Setter for store-model-features-after-training flag
store_model | whether model should be stored after training |
Definition at line 114 of file Machine.cpp.
set w
src_w | new w |
src_w_dim | dimension of new w |
Definition at line 89 of file OnlineLinearMachine.h.
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Set weight vector from a float64_t vector
src_w | new w |
src_w_dim | dimension of new w |
Definition at line 100 of file OnlineLinearMachine.h.
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virtualinherited |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
Reimplemented in CGaussianKernel.
Definition at line 226 of file SGObject.cpp.
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Start training of the online machine, sub-class should override this if some preparations are to be done
Reimplemented in COnlineLibLinear.
Definition at line 192 of file OnlineLinearMachine.h.
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Stop training of the online machine, sub-class should override this if some clean up is needed
Reimplemented in COnlineLibLinear.
Definition at line 197 of file OnlineLinearMachine.h.
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protectedvirtualinherited |
Stores feature data of underlying model. After this method has been called, it is possible to change the machine's feature data and call apply(), which is then performed on the training feature data that is part of the machine's model.
Base method, has to be implemented in order to allow cross-validation and model selection.
NOT IMPLEMENTED! Has to be done in subclasses
Reimplemented in CKernelMachine, CKNN, CLinearMachine, CLinearMulticlassMachine, CKMeansBase, CTreeMachine< T >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CGaussianProcessMachine, CHierarchical, CDistanceMachine, CKernelMulticlassMachine, and CLinearStructuredOutputMachine.
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inherited |
Subscribe a parameter observer to watch over params
Definition at line 811 of file SGObject.cpp.
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virtualinherited |
Reimplemented in CKernelMachine.
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virtual |
train 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 69 of file OnlineSVMSGD.cpp.
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virtualinherited |
train on one example
feature | the feature object containing the current example. Note that get_next_example is already called so relevalent methods like dot() and dense_dot() can be directly called. WARN: this function should only process ONE example, and get_next_example() should NEVER be called here. Use the label passed in the 2nd parameter, instead of get_label() from feature, because sometimes the features might not have associated labels or the caller might want to provide some other labels. |
label | label of this example |
Reimplemented in COnlineLibLinear.
Definition at line 208 of file OnlineLinearMachine.h.
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.
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protectedvirtualinherited |
Train classifier
data | Training data, can be avoided if already initialized with it |
Reimplemented from CMachine.
Reimplemented in CVowpalWabbit.
Definition at line 88 of file OnlineLinearMachine.cpp.
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protectedvirtualinherited |
whether train require labels
Reimplemented from CMachine.
Definition at line 229 of file OnlineLinearMachine.h.
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inherited |
decrement reference counter and deallocate object if refcount is zero before or after decrementing it
Definition at line 200 of file SGObject.cpp.
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inherited |
unset generic type
this has to be called in classes specializing a template class
Definition at line 337 of file SGObject.cpp.
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virtualinherited |
Updates the hash of current parameter combination
Definition at line 282 of file SGObject.cpp.
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protectedinherited |
bias
Definition at line 235 of file OnlineLinearMachine.h.
|
protectedinherited |
features
Definition at line 237 of file OnlineLinearMachine.h.
|
inherited |
io
Definition at line 600 of file SGObject.h.
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protectedinherited |
|
protectedinherited |
|
inherited |
parameters wrt which we can compute gradients
Definition at line 615 of file SGObject.h.
|
inherited |
Hash of parameter values
Definition at line 618 of file SGObject.h.
|
protectedinherited |
|
inherited |
model selection parameters
Definition at line 612 of file SGObject.h.
|
protectedinherited |
|
inherited |
parameters
Definition at line 609 of file SGObject.h.
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
w
Definition at line 233 of file OnlineLinearMachine.h.
|
inherited |
parallel
Definition at line 603 of file SGObject.h.
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inherited |
version
Definition at line 606 of file SGObject.h.