Public Member Functions | Public Attributes | Protected Member Functions | Protected Attributes

CDualLibQPBMSOSVM Class Reference


Detailed Description

Class DualLibQPBMSOSVM that uses Bundle Methods for Regularized Risk Minimization algorithms for structured output (SO) problems [1] presented in [2].

[1] Tsochantaridis, I., Hofmann, T., Joachims, T., Altun, Y. Support Vector Machine Learning for Interdependent and Structured Ouput Spaces. http://www.cs.cornell.edu/People/tj/publications/tsochantaridis_etal_04a.pdf

[2] Teo, C.H., Vishwanathan, S.V.N, Smola, A. and Quoc, V.Le. Bundle Methods for Regularized Risk Minimization http://users.cecs.anu.edu.au/~chteo/pub/TeoVisSmoLe10.pdf

Definition at line 46 of file DualLibQPBMSOSVM.h.

Inheritance diagram for CDualLibQPBMSOSVM:
Inheritance graph
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List of all members.

Public Member Functions

 CDualLibQPBMSOSVM ()
 CDualLibQPBMSOSVM (CStructuredModel *model, CLossFunction *loss, CStructuredLabels *labs, float64_t _lambda, SGVector< float64_t > W=0)
 ~CDualLibQPBMSOSVM ()
virtual const char * get_name () const
void set_lambda (float64_t _lambda)
float64_t get_lambda ()
void set_TolRel (float64_t TolRel)
float64_t get_TolRel ()
void set_TolAbs (float64_t TolAbs)
float64_t get_TolAbs ()
void set_BufSize (uint32_t BufSize)
uint32_t get_BufSize ()
void set_cleanICP (bool cleanICP)
bool get_cleanICP ()
void set_cleanAfter (uint32_t cleanAfter)
uint32_t get_cleanAfter ()
void set_K (float64_t K)
float64_t get_K ()
void set_Tmax (uint32_t Tmax)
uint32_t get_Tmax ()
void set_cp_models (uint32_t cp_models)
uint32_t get_cp_models ()
void set_verbose (bool verbose)
bool get_verbose ()
bmrm_return_value_T get_result ()
ESolver get_solver ()
void set_solver (ESolver solver)
void set_w (SGVector< float64_t > W)
void set_features (CFeatures *f)
CFeaturesget_features () const
SGVector< float64_tget_w () const
virtual CStructuredLabelsapply_structured (CFeatures *data=NULL)
 MACHINE_PROBLEM_TYPE (PT_STRUCTURED)
void set_model (CStructuredModel *model)
void set_loss (CLossFunction *loss)
virtual bool train (CFeatures *data=NULL)
virtual CLabelsapply (CFeatures *data=NULL)
virtual CBinaryLabelsapply_binary (CFeatures *data=NULL)
virtual CRegressionLabelsapply_regression (CFeatures *data=NULL)
virtual CMulticlassLabelsapply_multiclass (CFeatures *data=NULL)
virtual CLatentLabelsapply_latent (CFeatures *data=NULL)
virtual void set_labels (CLabels *lab)
virtual CLabelsget_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 CLabelsapply_locked (SGVector< index_t > indices)
virtual CBinaryLabelsapply_locked_binary (SGVector< index_t > indices)
virtual CRegressionLabelsapply_locked_regression (SGVector< index_t > indices)
virtual CMulticlassLabelsapply_locked_multiclass (SGVector< index_t > indices)
virtual CStructuredLabelsapply_locked_structured (SGVector< index_t > indices)
virtual CLatentLabelsapply_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
virtual CMachineclone ()
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_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)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_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

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

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
virtual TParametermigrate (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

CFeaturesm_features
SGVector< float64_tm_w
CStructuredModelm_model
CLossFunctionm_loss
float64_t m_max_train_time
CLabelsm_labels
ESolverType m_solver_type
bool m_store_model_features
bool m_data_locked

Constructor & Destructor Documentation

default constructor

Definition at line 17 of file DualLibQPBMSOSVM.cpp.

CDualLibQPBMSOSVM ( CStructuredModel model,
CLossFunction loss,
CStructuredLabels labs,
float64_t  _lambda,
SGVector< float64_t W = 0 
)

constructor

Parameters:
model Structured Model
loss Loss function
labs Structured labels
_lambda Regularization constant
W initial solution of weight vector

Definition at line 22 of file DualLibQPBMSOSVM.cpp.

destructor

Definition at line 60 of file DualLibQPBMSOSVM.cpp.


Member Function Documentation

CLabels * apply ( CFeatures data = NULL  )  [virtual, inherited]

apply machine to data if data is not specified apply to the current features

Parameters:
data (test)data to be classified
Returns:
classified labels

Definition at line 162 of file Machine.cpp.

CBinaryLabels * apply_binary ( CFeatures data = NULL  )  [virtual, inherited]

apply machine to data in means of binary classification problem

Reimplemented in CPluginEstimate, CWDSVMOcas, CKernelMachine, CLinearMachine, COnlineLinearMachine, CDomainAdaptationSVM, and CDomainAdaptationSVMLinear.

Definition at line 218 of file Machine.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.

CLabels * apply_locked ( SGVector< index_t indices  )  [virtual, inherited]

Applies a locked machine on a set of indices. Error if machine is not locked

Parameters:
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.

virtual float64_t apply_one ( int32_t  i  )  [virtual, inherited]
CRegressionLabels * apply_regression ( CFeatures data = NULL  )  [virtual, inherited]

apply machine to data in means of regression problem

Reimplemented in CWDSVMOcas, CKernelMachine, CLinearMachine, COnlineLinearMachine, and CGaussianProcessRegression.

Definition at line 224 of file Machine.cpp.

CStructuredLabels * apply_structured ( CFeatures data = NULL  )  [virtual, inherited]

apply structured machine to data for Structured Output (SO) problem

Parameters:
data (test)data to be classified
Returns:
classified 'labels'

Reimplemented from CMachine.

Definition at line 50 of file LinearStructuredOutputMachine.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.

Parameters:
dict dictionary of parameters to be built.

Definition at line 1201 of file SGObject.cpp.

virtual CMachine* clone (  )  [virtual, inherited]

clone

Reimplemented in CKernelMachine, and CLinearMachine.

Definition at line 294 of file Machine.h.

void data_lock ( CLabels labs,
CFeatures features 
) [virtual, inherited]

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

Parameters:
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.

uint32_t get_BufSize (  ) 

get size of cutting plane buffer

Returns:
Size of the cutting plane buffer

Definition at line 120 of file DualLibQPBMSOSVM.h.

EMachineType get_classifier_type (  )  [virtual, inherited]
uint32_t get_cleanAfter (  ) 

get number of iterations for cleaning ICP

Returns:
Number of iterations that inactive cutting planes has to be inactive for to be removed

Definition at line 147 of file DualLibQPBMSOSVM.h.

bool get_cleanICP (  ) 

get ICP removal flag

Returns:
Status of inactive cutting plane removal feature (enabled/disabled)

Definition at line 133 of file DualLibQPBMSOSVM.h.

uint32_t get_cp_models (  ) 

get number of cutting plane models

Returns:
Number of cutting plane models

Definition at line 183 of file DualLibQPBMSOSVM.h.

CFeatures * get_features (  )  const [inherited]

get features

Returns:
features

Definition at line 40 of file LinearStructuredOutputMachine.cpp.

SGIO * get_global_io (  )  [inherited]

get the io object

Returns:
io object

Definition at line 224 of file SGObject.cpp.

Parallel * get_global_parallel (  )  [inherited]

get the parallel object

Returns:
parallel object

Definition at line 259 of file SGObject.cpp.

Version * get_global_version (  )  [inherited]

get the version object

Returns:
version object

Definition at line 272 of file SGObject.cpp.

float64_t get_K (  ) 

get K

Returns:
K

Definition at line 159 of file DualLibQPBMSOSVM.h.

CLabels * get_labels (  )  [virtual, inherited]

get labels

Returns:
labels

Definition at line 86 of file Machine.cpp.

float64_t get_lambda (  ) 

get lambda

Returns:
Regularization constant

Definition at line 83 of file DualLibQPBMSOSVM.h.

virtual EProblemType get_machine_problem_type (  )  const [virtual, inherited]

returns type of problem machine solves

Reimplemented in CBaseMulticlassMachine.

Definition at line 287 of file Machine.h.

float64_t get_max_train_time (  )  [inherited]

get maximum training time

Returns:
maximum training time

Definition at line 97 of file Machine.cpp.

SGStringList< char > get_modelsel_names (  )  [inherited]
Returns:
vector of names of all parameters which are registered for model selection

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

Parameters:
param_name name of the parameter
Returns:
description 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

Parameters:
param_name name of model selection parameter
Returns:
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1145 of file SGObject.cpp.

virtual const char* get_name (  )  const [virtual]
Returns:
name of SGSerializable

Reimplemented from CLinearStructuredOutputMachine.

Definition at line 71 of file DualLibQPBMSOSVM.h.

bmrm_return_value_T get_result (  ) 

get bmrm result

Returns:
Result returned from Bundle Method algorithm

Definition at line 201 of file DualLibQPBMSOSVM.h.

ESolver get_solver (  ) 

get training algorithm

Returns:
Type of Bundle Method solver used for training

Definition at line 207 of file DualLibQPBMSOSVM.h.

ESolverType get_solver_type (  )  [inherited]

get solver type

Returns:
solver

Definition at line 112 of file Machine.cpp.

uint32_t get_Tmax (  ) 

get Tmax

Returns:
Tmax

Definition at line 171 of file DualLibQPBMSOSVM.h.

float64_t get_TolAbs (  ) 

get absolute tolerance

Returns:
Absolute tolerance

Definition at line 107 of file DualLibQPBMSOSVM.h.

float64_t get_TolRel (  ) 

get relative tolerance

Returns:
Relative tolerance

Definition at line 95 of file DualLibQPBMSOSVM.h.

bool get_verbose (  ) 

get verbose

Returns:
Status of screen output (enabled/disabled)

Definition at line 195 of file DualLibQPBMSOSVM.h.

SGVector< float64_t > get_w (  )  const [inherited]

get w

Returns:
w

Definition at line 45 of file LinearStructuredOutputMachine.cpp.

bool is_data_locked (  )  const [inherited]
Returns:
whether this machine is locked

Definition at line 284 of file Machine.h.

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.

Parameters:
generic set to the type of the generic if returning TRUE
Returns:
TRUE if a class template.

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.

Parameters:
lab the labels being checked, guaranteed to be non-NULL

Reimplemented in CBaseMulticlassMachine.

Definition at line 343 of file Machine.h.

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)

Parameters:
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
Returns:
(sorted) array of created TParameter instances with file data

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

Parameters:
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
Returns:
new array with TParameter instances with the attached data

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!

Parameters:
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)
Returns:
TRUE if done, otherwise FALSE

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.

Exceptions:
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.

Exceptions:
ShogunException Will be thrown if an error occurres.

Definition at line 1028 of file SGObject.cpp.

MACHINE_PROBLEM_TYPE ( PT_STRUCTURED   )  [inherited]

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

Parameters:
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

Parameters:
param_base set of TParameter instances to use for migration
target parameter info for the resulting TParameter
Returns:
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

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)

Parameters:
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.

virtual void post_lock ( CLabels labs,
CFeatures features 
) [virtual, inherited]

post lock

Reimplemented in CMultitaskCompositeMachine, and CMultitaskLinearMachine.

Definition at line 275 of file Machine.h.

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

Parameters:
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.

Parameters:
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)
Returns:
TRUE if done, otherwise FALSE

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.

Exceptions:
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.

Exceptions:
ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1038 of file SGObject.cpp.

void set_BufSize ( uint32_t  BufSize  ) 

set size of cutting plane buffer

Parameters:
BufSize Size of the cutting plane buffer (i.e. maximal number of iterations)

Definition at line 114 of file DualLibQPBMSOSVM.h.

void set_cleanAfter ( uint32_t  cleanAfter  ) 

set number of iterations for cleaning ICP

Parameters:
cleanAfter Specifies number of iterations that inactive cutting planes has to be inactive for to be removed

Definition at line 140 of file DualLibQPBMSOSVM.h.

void set_cleanICP ( bool  cleanICP  ) 

set ICP removal flag

Parameters:
cleanICP Flag that enables/disables inactive cutting plane removal feature

Definition at line 127 of file DualLibQPBMSOSVM.h.

void set_cp_models ( uint32_t  cp_models  ) 

set number of cutting plane models

Parameters:
cp_models Number of cutting plane models

Definition at line 177 of file DualLibQPBMSOSVM.h.

void set_features ( CFeatures f  )  [inherited]

set features

Parameters:
f features

Definition at line 35 of file LinearStructuredOutputMachine.cpp.

void set_generic< floatmax_t > (  )  [inherited]

set generic type to T

void set_global_io ( SGIO io  )  [inherited]

set the io object

Parameters:
io io object to use

Definition at line 217 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel  )  [inherited]

set the parallel object

Parameters:
parallel parallel object to use

Definition at line 230 of file SGObject.cpp.

void set_global_version ( Version version  )  [inherited]

set the version object

Parameters:
version version object to use

Definition at line 265 of file SGObject.cpp.

void set_K ( float64_t  K  ) 

set K

Parameters:
K Parameter K

Definition at line 153 of file DualLibQPBMSOSVM.h.

void set_labels ( CLabels lab  )  [virtual, inherited]

set labels

Parameters:
lab labels

Reimplemented in CMulticlassMachine, and CRelaxedTree.

Definition at line 75 of file Machine.cpp.

void set_lambda ( float64_t  _lambda  ) 

set lambda

Parameters:
_lambda Regularization constant

Definition at line 77 of file DualLibQPBMSOSVM.h.

void set_loss ( CLossFunction loss  )  [inherited]

set loss function

Parameters:
loss loss function to set

Definition at line 46 of file StructuredOutputMachine.cpp.

void set_max_train_time ( float64_t  t  )  [inherited]

set maximum training time

Parameters:
t maximimum training time

Definition at line 92 of file Machine.cpp.

void set_model ( CStructuredModel model  )  [inherited]

set structured model

Parameters:
model structured model to set

Definition at line 39 of file StructuredOutputMachine.cpp.

void set_solver ( ESolver  solver  ) 

set training algorithm

Parameters:
solver Type of Bundle Method solver used for training

Definition at line 213 of file DualLibQPBMSOSVM.h.

void set_solver_type ( ESolverType  st  )  [inherited]

set solver type

Parameters:
st solver type

Definition at line 107 of file Machine.cpp.

void set_store_model_features ( bool  store_model  )  [virtual, inherited]

Setter for store-model-features-after-training flag

Parameters:
store_model whether model should be stored after training

Definition at line 117 of file Machine.cpp.

void set_Tmax ( uint32_t  Tmax  ) 

set Tmax

Parameters:
Tmax Parameter Tmax

Definition at line 165 of file DualLibQPBMSOSVM.h.

void set_TolAbs ( float64_t  TolAbs  ) 

set absolute tolerance

Parameters:
TolAbs Absolute tolerance

Definition at line 101 of file DualLibQPBMSOSVM.h.

void set_TolRel ( float64_t  TolRel  ) 

set relative tolerance

Parameters:
TolRel Relative tolerance

Definition at line 89 of file DualLibQPBMSOSVM.h.

void set_verbose ( bool  verbose  ) 

set verbose

Parameters:
verbose Flag enabling/disabling screen output

Definition at line 189 of file DualLibQPBMSOSVM.h.

void set_w ( SGVector< float64_t W  ) 

set initial value of weight vector w

Parameters:
W initial weight vector

Definition at line 219 of file DualLibQPBMSOSVM.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. 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 CHierarchical, CKMeans, CDistanceMachine, CKernelMachine, CKernelMulticlassMachine, CLinearMachine, CLinearMulticlassMachine, and CKNN.

Definition at line 330 of file Machine.h.

virtual bool supports_locking (  )  const [virtual, inherited]
Returns:
whether this machine supports locking

Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.

Definition at line 281 of file Machine.h.

bool train ( CFeatures data = NULL  )  [virtual, inherited]

train machine

Parameters:
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.
Returns:
whether training was successful

Reimplemented in COnlineSVMSGD, CSGDQN, and CRelaxedTree.

Definition at line 49 of file Machine.cpp.

virtual bool train_locked ( SGVector< index_t indices  )  [virtual, inherited]

Trains a locked machine on a set of indices. Error if machine is not locked

NOT IMPLEMENTED

Parameters:
indices index vector (of locked features) that is used for training
Returns:
whether training was successful

Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.

Definition at line 227 of file Machine.h.

bool train_machine ( CFeatures data = NULL  )  [protected, virtual]

train dual SO-SVM

Reimplemented from CMachine.

Definition at line 84 of file DualLibQPBMSOSVM.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.

Definition at line 349 of file Machine.h.

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.

bool update_parameter_hash (  )  [protected, virtual, inherited]

Updates the hash of current parameter combination.

Returns:
bool if parameter combination has changed since last update.

Definition at line 237 of file SGObject.cpp.


Member Data Documentation

SGIO* io [inherited]

io

Definition at line 462 of file SGObject.h.

bool m_data_locked [protected, inherited]

whether data is locked

Definition at line 365 of file Machine.h.

CFeatures* m_features [protected, inherited]

feature vectors

Definition at line 78 of file LinearStructuredOutputMachine.h.

uint32_t m_hash [inherited]

Hash of parameter values

Definition at line 480 of file SGObject.h.

CLabels* m_labels [protected, inherited]

labels

Definition at line 356 of file Machine.h.

CLossFunction* m_loss [protected, inherited]

the general loss function

Definition at line 73 of file StructuredOutputMachine.h.

float64_t m_max_train_time [protected, inherited]

maximum training time

Definition at line 353 of file Machine.h.

CStructuredModel* m_model [protected, inherited]

the model that contains the application dependent modules

Definition at line 70 of file StructuredOutputMachine.h.

model selection parameters

Definition at line 474 of file SGObject.h.

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]

solver type

Definition at line 359 of file Machine.h.

bool m_store_model_features [protected, inherited]

whether model features should be stored after training

Definition at line 362 of file Machine.h.

SGVector< float64_t > m_w [protected, inherited]

weight vector

Definition at line 81 of file LinearStructuredOutputMachine.h.

Parallel* parallel [inherited]

parallel

Definition at line 465 of file SGObject.h.

Version* version [inherited]

version

Definition at line 468 of file SGObject.h.


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