SHOGUN
6.1.3
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A generic learning machine interface.
A machine takes as input CFeatures and CLabels (by default). Later subclasses may specialize the machine to e.g. require labels and a kernel or labels and (real-valued) features.
A machine needs to override the train() function for training, the functions apply(idx) (optionally apply() to predict on the whole set of examples) and the load and save routines.
Machines may support locking. This means that given some data, the machine can be locked on this data to speed up computations. E.g. a kernel machine may precompute its kernel. Only train_locked and apply_locked are available when locked. There are methods for checking whether a machine supports locking.
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 | |
CMachine () | |
virtual | ~CMachine () |
virtual bool | train (CFeatures *data=NULL) |
virtual CLabels * | apply (CFeatures *data=NULL) |
virtual CBinaryLabels * | apply_binary (CFeatures *data=NULL) |
virtual CRegressionLabels * | apply_regression (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 () |
virtual EMachineType | get_classifier_type () |
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 float64_t | apply_one (int32_t i) |
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 () |
virtual const char * | get_name () const |
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 | |
virtual bool | train_machine (CFeatures *data=NULL) |
virtual void | store_model_features () |
virtual bool | is_label_valid (CLabels *lab) const |
virtual bool | train_require_labels () 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 | |
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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Definition at line 130 of file SGObject.h.
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Definition at line 127 of file SGObject.h.
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Definition at line 133 of file SGObject.h.
CMachine | ( | ) |
constructor
Definition at line 19 of file Machine.cpp.
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destructor
Definition at line 38 of file Machine.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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apply machine to data in means of binary classification problem
Reimplemented in CKernelMachine, CNeuralNetwork, COnlineLinearMachine, CLinearMachine, CGaussianProcessClassification, CDomainAdaptationSVMLinear, CDomainAdaptationSVM, CPluginEstimate, and CBaggingMachine.
Definition at line 215 of file Machine.cpp.
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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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applies to one vector
Reimplemented in CKernelMachine, CRelaxedTree, COnlineLinearMachine, CLinearMachine, CKNN, CMulticlassMachine, CDistanceMachine, CScatterSVM, CGaussianNaiveBayes, and CPluginEstimate.
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apply machine to data in means of regression problem
Reimplemented in CKernelMachine, CNeuralNetwork, CLinearMachine, COnlineLinearMachine, CCHAIDTree, CStochasticGBMachine, CCARTree, CGaussianProcessRegression, and CBaggingMachine.
Definition at line 221 of file Machine.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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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.
SG_FORCED_INLINE bool cancel_computation | ( | ) | const |
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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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get classifier type
Reimplemented in CLaRank, CSVMLight, CNeuralNetwork, CCCSOSVM, CLeastAngleRegression, CLDA, CQDA, CLibLinearMTL, CBaggingMachine, CLibLinear, CGaussianProcessClassification, CKernelRidgeRegression, CKNN, CLibSVR, CGaussianNaiveBayes, CSVRLight, CMCLDA, CLinearRidgeRegression, CScatterSVM, CGaussianProcessRegression, CSGDQN, CSVMSGD, CMKLClassification, COnlineSVMSGD, CLeastSquaresRegression, CMKLRegression, CDomainAdaptationSVMLinear, CMKLMulticlass, CKMeansBase, CHierarchical, CMKLOneClass, CLibSVM, CStochasticSOSVM, CDomainAdaptationSVM, CLPBoost, CPerceptron, CAveragedPerceptron, CFWSOSVM, CNewtonSVM, CLPM, CGMNPSVM, CSVMLightOneClass, CMulticlassLibSVM, CLibSVMOneClass, CMPDSVM, CGNPPSVM, and CCPLEXSVM.
Definition at line 99 of file Machine.cpp.
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returns type of problem machine solves
Reimplemented in CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree, and CBaseMulticlassMachine.
float64_t get_max_train_time | ( | ) |
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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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Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.
Implements CSGObject.
Reimplemented in CSVMLight, CLaRank, CMKL, CSVM, CNeuralNetwork, CMulticlassSVM, CPluginEstimate, CVowpalWabbit, CSVRLight, CKNN, CLeastAngleRegression, COnlineLinearMachine, CLDA, CDeepAutoencoder, CMKLMulticlass, CAutoencoder, CLibLinearMTL, CLinearMachine, COnlineSVMSGD, CLibLinear, CQDA, CKMeansBase, CSVMSGD, CMulticlassMachine, CSGDQN, CBaggingMachine, CDomainAdaptationSVMLinear, CGaussianProcessClassification, CCHAIDTree, CMCLDA, COnlineLibLinear, CCARTree, CKernelRidgeRegression, CHierarchical, CKRRNystrom, CLibSVR, CNewtonSVM, CLPBoost, CScatterSVM, CLinearRidgeRegression, CDomainAdaptationSVM, CKNNSolver, CC45ClassifierTree, CLPM, CID3ClassifierTree, CRandomForest, CNearestCentroid, CGaussianNaiveBayes, CGaussianProcessRegression, CKernelMachine, CDistanceMachine, CStructuredOutputMachine, CGaussianProcessMachine, CLibLinearRegression, CPerceptron, CStochasticGBMachine, CTreeMachine< T >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CLinearStructuredOutputMachine, CKMeans, CAveragedPerceptron, CNbodyTree, CLeastSquaresRegression, CLinearLatentMachine, CGMNPSVM, CLibSVM, CBallTree, CKDTree, CLinearMulticlassMachine, CRandomCARTree, CCCSOSVM, CMulticlassLibLinear, CSVMLightOneClass, CKernelStructuredOutputMachine, CVwConditionalProbabilityTree, CMKLClassification, CKDTREEKNNSolver, CStochasticSOSVM, CKMeansMiniBatch, CCoverTreeKNNSolver, CMulticlassLibSVM, CMKLRegression, CBruteKNNSolver, CBalancedConditionalProbabilityTree, CMKLOneClass, CLibSVMOneClass, CMPDSVM, CKernelMulticlassMachine, CConditionalProbabilityTree, CRelaxedTree, CFWSOSVM, CDomainAdaptationMulticlassLibLinear, CShareBoost, CGNPPSVM, CNativeMulticlassMachine, CBaseMulticlassMachine, and CRandomConditionalProbabilityTree.
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ESolverType get_solver_type | ( | ) |
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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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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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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.
bool is_data_locked | ( | ) | const |
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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 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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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 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.
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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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Definition at line 296 of file SGObject.cpp.
SG_FORCED_INLINE void pause_computation | ( | ) |
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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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prints registered parameters out
prefix | prefix for members |
Definition at line 342 of file SGObject.cpp.
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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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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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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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SG_FORCED_INLINE void resume_computation | ( | ) |
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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 |
Definition at line 348 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 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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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_max_train_time | ( | float64_t | t | ) |
set maximum training time
t | maximimum training time |
Definition at line 89 of file Machine.cpp.
void set_solver_type | ( | ESolverType | st | ) |
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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.
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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 226 of file SGObject.cpp.
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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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Subscribe a parameter observer to watch over params
Definition at line 811 of file SGObject.cpp.
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Reimplemented in CKernelMachine.
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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 CRelaxedTree, CAutoencoder, CLinearMachine, CSGDQN, and COnlineSVMSGD.
Definition at line 43 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.
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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) |
NOT IMPLEMENTED!
Reimplemented in CSVMLight, CNeuralNetwork, CLaRank, CLibLinearMTL, CMKL, CKNN, CCARTree, CCHAIDTree, CSVRLight, COnlineLinearMachine, CPluginEstimate, CRelaxedTree, CLeastAngleRegression, CLDA, CLibLinear, CQDA, CCCSOSVM, CMulticlassMachine, CMKLMulticlass, CC45ClassifierTree, CLibLinearRegression, CSVMSGD, CStochasticGBMachine, CMulticlassLibLinear, CVowpalWabbit, CRandomForest, CMCLDA, CGaussianProcessClassification, CDomainAdaptationSVMLinear, CBaggingMachine, CID3ClassifierTree, CKernelRidgeRegression, CHierarchical, CLinearLatentMachine, CLibSVR, CNewtonSVM, CLPBoost, CDomainAdaptationSVM, CScatterSVM, CStochasticSOSVM, CLinearRidgeRegression, CLPM, CGaussianNaiveBayes, CFWSOSVM, CNearestCentroid, CKMeansMiniBatch, CVwConditionalProbabilityTree, CConditionalProbabilityTree, CGaussianProcessRegression, CPerceptron, CAveragedPerceptron, CLibSVM, CGMNPSVM, CSVMLightOneClass, CShareBoost, CLibSVMOneClass, CMulticlassLibSVM, CMPDSVM, CGNPPSVM, and CCPLEXSVM.
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returns whether machine require labels for training
Reimplemented in COnlineLinearMachine, CKMeansBase, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree, and CLibSVMOneClass.
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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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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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Updates the hash of current parameter combination
Definition at line 282 of file SGObject.cpp.
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io
Definition at line 600 of file SGObject.h.
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parameters wrt which we can compute gradients
Definition at line 615 of file SGObject.h.
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Hash of parameter values
Definition at line 618 of file SGObject.h.
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model selection parameters
Definition at line 612 of file SGObject.h.
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parameters
Definition at line 609 of file SGObject.h.
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protected |
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protected |
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protected |
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parallel
Definition at line 603 of file SGObject.h.
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version
Definition at line 606 of file SGObject.h.