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

CMulticlassOCAS Class Reference


Detailed Description

multiclass OCAS wrapper

Definition at line 23 of file MulticlassOCAS.h.

Inheritance diagram for CMulticlassOCAS:
Inheritance graph
[legend]

List of all members.

Public Member Functions

 CMulticlassOCAS ()
 CMulticlassOCAS (float64_t C, CDotFeatures *features, CLabels *labs)
virtual ~CMulticlassOCAS ()
virtual const char * get_name () const
void set_C (float64_t C)
float64_t get_C () const
void set_epsilon (float64_t epsilon)
float64_t get_epsilon () const
void set_max_iter (int32_t max_iter)
int32_t get_max_iter () const
void set_method (int32_t method)
int32_t get_method () const
void set_buf_size (int32_t buf_size)
int32_t get_buf_size () const
void set_features (CDotFeatures *f)
CDotFeaturesget_features () const
virtual void set_labels (CLabels *lab)
bool set_machine (int32_t num, CMachine *machine)
CMachineget_machine (int32_t num) const
virtual CBinaryLabelsget_submachine_outputs (int32_t i)
virtual float64_t get_submachine_output (int32_t i, int32_t num)
virtual CMulticlassLabelsapply_multiclass (CFeatures *data=NULL)
virtual
CMulticlassMultipleOutputLabels
apply_multiclass_multiple_output (CFeatures *data=NULL, int32_t n_outputs=5)
virtual float64_t apply_one (int32_t vec_idx)
CMulticlassStrategyget_multiclass_strategy () const
CRejectionStrategyget_rejection_strategy () const
void set_rejection_strategy (CRejectionStrategy *rejection_strategy)
int32_t get_num_machines () const
virtual EProblemType get_machine_problem_type () const
virtual bool is_label_valid (CLabels *lab) const
virtual bool train (CFeatures *data=NULL)
virtual CLabelsapply (CFeatures *data=NULL)
virtual CBinaryLabelsapply_binary (CFeatures *data=NULL)
virtual CRegressionLabelsapply_regression (CFeatures *data=NULL)
virtual CStructuredLabelsapply_structured (CFeatures *data=NULL)
virtual CLatentLabelsapply_latent (CFeatures *data=NULL)
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 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 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

virtual bool train_machine (CFeatures *data=NULL)
virtual bool init_machine_for_train (CFeatures *data)
virtual bool init_machines_for_apply (CFeatures *data)
virtual bool is_ready ()
virtual CMachineget_machine_from_trained (CMachine *machine)
virtual int32_t get_num_rhs_vectors ()
virtual void add_machine_subset (SGVector< index_t > subset)
virtual void remove_machine_subset ()
virtual void store_model_features ()
void init_strategy ()
void clear_machines ()
virtual bool is_acceptable_machine (CMachine *machine)
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 ()

Static Protected Member Functions

static float64_t msvm_update_W (float64_t t, void *user_data)
static void msvm_full_compute_W (float64_t *sq_norm_W, float64_t *dp_WoldW, float64_t *alpha, uint32_t nSel, void *user_data)
static int msvm_full_add_new_cut (float64_t *new_col_H, uint32_t *new_cut, uint32_t nSel, void *user_data)
static int msvm_full_compute_output (float64_t *output, void *user_data)
static int msvm_sort_data (float64_t *vals, float64_t *data, uint32_t size)
static void msvm_print (ocas_return_value_T value)

Protected Attributes

float64_t m_C
float64_t m_epsilon
int32_t m_max_iter
int32_t m_method
int32_t m_buf_size
CDotFeaturesm_features
CMulticlassStrategym_multiclass_strategy
CMachinem_machine
CDynamicObjectArraym_machines
float64_t m_max_train_time
CLabelsm_labels
ESolverType m_solver_type
bool m_store_model_features
bool m_data_locked

Constructor & Destructor Documentation

CMulticlassOCAS (  ) 

default constructor

Definition at line 33 of file MulticlassOCAS.cpp.

CMulticlassOCAS ( float64_t  C,
CDotFeatures features,
CLabels labs 
)

standard constructor

Parameters:
C C regularication constant value
features features
labs labels

Definition at line 44 of file MulticlassOCAS.cpp.

~CMulticlassOCAS (  )  [virtual]

destructor

Definition at line 63 of file MulticlassOCAS.cpp.


Member Function Documentation

virtual void add_machine_subset ( SGVector< index_t subset  )  [protected, virtual, inherited]

set subset to the features of the machine, deletes old one

Parameters:
subset subset instance to set

Implements CMulticlassMachine.

Definition at line 143 of file LinearMulticlassMachine.h.

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]

classify all examples

Returns:
resulting labels

Reimplemented from CMachine.

Reimplemented in CGaussianNaiveBayes, and CQDA.

Definition at line 92 of file MulticlassMachine.cpp.

CMulticlassMultipleOutputLabels * apply_multiclass_multiple_output ( CFeatures data = NULL,
int32_t  n_outputs = 5 
) [virtual, inherited]

classify all examples with multiple output

Returns:
resulting labels

Definition at line 146 of file MulticlassMachine.cpp.

float64_t apply_one ( int32_t  vec_idx  )  [virtual, inherited]

classify one example

Parameters:
vec_idx 
Returns:
label

Reimplemented from CMachine.

Reimplemented in CGaussianNaiveBayes.

Definition at line 234 of file MulticlassMachine.cpp.

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 machine to data in means of SO classification problem

Reimplemented in CLinearStructuredOutputMachine.

Definition at line 236 of file Machine.cpp.

void build_parameter_dictionary ( CMap< TParameter *, CSGObject * > &  dict  )  [inherited]

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters:
dict dictionary of parameters to be built.

Definition at line 1201 of file SGObject.cpp.

void clear_machines (  )  [protected, inherited]

clear machines

Reimplemented in CNativeMulticlassMachine.

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.

int32_t get_buf_size (  )  const

get buf size

Returns:
buf_size value

Definition at line 110 of file MulticlassOCAS.h.

float64_t get_C (  )  const

get C

Returns:
C value

Definition at line 58 of file MulticlassOCAS.h.

EMachineType get_classifier_type (  )  [virtual, inherited]
float64_t get_epsilon (  )  const

get epsilon

Returns:
epsilon value

Definition at line 71 of file MulticlassOCAS.h.

CDotFeatures* get_features (  )  const [inherited]

get features

Returns:
features

Definition at line 78 of file LinearMulticlassMachine.h.

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.

CLabels * get_labels (  )  [virtual, inherited]

get labels

Returns:
labels

Definition at line 86 of file Machine.cpp.

CMachine* get_machine ( int32_t  num  )  const [inherited]

get machine

Parameters:
num index of machine to get
Returns:
SVM at number num

Definition at line 71 of file MulticlassMachine.h.

virtual CMachine* get_machine_from_trained ( CMachine machine  )  [protected, virtual, inherited]

construct linear machine from given linear machine

Implements CMulticlassMachine.

Definition at line 128 of file LinearMulticlassMachine.h.

virtual EProblemType get_machine_problem_type (  )  const [virtual, inherited]

get problem type

Reimplemented from CMachine.

Definition at line 46 of file BaseMulticlassMachine.h.

int32_t get_max_iter (  )  const

get max iter

Returns:
max iter value

Definition at line 84 of file MulticlassOCAS.h.

float64_t get_max_train_time (  )  [inherited]

get maximum training time

Returns:
maximum training time

Definition at line 97 of file Machine.cpp.

int32_t get_method (  )  const

get method

Returns:
method value

Definition at line 97 of file MulticlassOCAS.h.

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.

CMulticlassStrategy* get_multiclass_strategy (  )  const [inherited]

get the type of multiclass'ness

Returns:
multiclass type one vs one etc

Definition at line 111 of file MulticlassMachine.h.

virtual const char* get_name (  )  const [virtual]

get name

Reimplemented from CLinearMulticlassMachine.

Definition at line 42 of file MulticlassOCAS.h.

int32_t get_num_machines (  )  const [inherited]

get number of machines

Returns:
number of machines

Definition at line 40 of file BaseMulticlassMachine.h.

virtual int32_t get_num_rhs_vectors (  )  [protected, virtual, inherited]

get number of rhs feature vectors

Implements CMulticlassMachine.

Definition at line 134 of file LinearMulticlassMachine.h.

CRejectionStrategy* get_rejection_strategy (  )  const [inherited]

returns rejection strategy

Returns:
rejection strategy

Definition at line 121 of file MulticlassMachine.h.

ESolverType get_solver_type (  )  [inherited]

get solver type

Returns:
solver

Definition at line 112 of file Machine.cpp.

float64_t get_submachine_output ( int32_t  i,
int32_t  num 
) [virtual, inherited]

get output of i-th submachine for num-th vector

Parameters:
i number of submachine
num number of feature vector
Returns:
output

Definition at line 79 of file MulticlassMachine.cpp.

CBinaryLabels * get_submachine_outputs ( int32_t  i  )  [virtual, inherited]

get outputs of i-th submachine

Parameters:
i number of submachine
Returns:
outputs

Reimplemented in CDomainAdaptationMulticlassLibLinear.

Definition at line 70 of file MulticlassMachine.cpp.

virtual bool init_machine_for_train ( CFeatures data  )  [protected, virtual, inherited]

init machine for train with setting features

Implements CMulticlassMachine.

Definition at line 87 of file LinearMulticlassMachine.h.

virtual bool init_machines_for_apply ( CFeatures data  )  [protected, virtual, inherited]

init machines for applying with setting features

Implements CMulticlassMachine.

Definition at line 101 of file LinearMulticlassMachine.h.

void init_strategy (  )  [protected, inherited]

init strategy

Reimplemented in CNativeMulticlassMachine.

Definition at line 64 of file MulticlassMachine.cpp.

virtual bool is_acceptable_machine ( CMachine machine  )  [protected, virtual, inherited]

whether the machine is acceptable in set_machine

Reimplemented in CNativeMulticlassMachine, and CMulticlassSVM.

Definition at line 176 of file MulticlassMachine.h.

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 [virtual, inherited]

check whether the labels is valid.

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

Reimplemented from CMachine.

Definition at line 55 of file BaseMulticlassMachine.h.

virtual bool is_ready (  )  [protected, virtual, inherited]

check features availability

Implements CMulticlassMachine.

Definition at line 119 of file LinearMulticlassMachine.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.

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.

int msvm_full_add_new_cut ( float64_t new_col_H,
uint32_t *  new_cut,
uint32_t  nSel,
void *  user_data 
) [static, protected]

full add new cut

Definition at line 192 of file MulticlassOCAS.cpp.

int msvm_full_compute_output ( float64_t output,
void *  user_data 
) [static, protected]

full compute output

Definition at line 238 of file MulticlassOCAS.cpp.

void msvm_full_compute_W ( float64_t sq_norm_W,
float64_t dp_WoldW,
float64_t alpha,
uint32_t  nSel,
void *  user_data 
) [static, protected]

full compute W

Definition at line 163 of file MulticlassOCAS.cpp.

void msvm_print ( ocas_return_value_T  value  )  [static, protected]

print nothing

Definition at line 265 of file MulticlassOCAS.cpp.

int msvm_sort_data ( float64_t vals,
float64_t data,
uint32_t  size 
) [static, protected]

sort

Definition at line 259 of file MulticlassOCAS.cpp.

float64_t msvm_update_W ( float64_t  t,
void *  user_data 
) [static, protected]

update W

Definition at line 148 of file MulticlassOCAS.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.

virtual void remove_machine_subset (  )  [protected, virtual, inherited]

deletes any subset set to the features of the machine

Implements CMulticlassMachine.

Definition at line 151 of file LinearMulticlassMachine.h.

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_buf_size ( int32_t  buf_size  ) 

set buf size

Parameters:
buf_size buf size value

Definition at line 102 of file MulticlassOCAS.h.

void set_C ( float64_t  C  ) 

set C

Parameters:
C C value

Definition at line 50 of file MulticlassOCAS.h.

void set_epsilon ( float64_t  epsilon  ) 

set epsilon

Parameters:
epsilon epsilon value

Definition at line 63 of file MulticlassOCAS.h.

void set_features ( CDotFeatures f  )  [inherited]

set features

Parameters:
f features

Definition at line 67 of file LinearMulticlassMachine.h.

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_labels ( CLabels lab  )  [virtual, inherited]

set labels

Parameters:
lab labels

Reimplemented from CMachine.

Definition at line 51 of file MulticlassMachine.cpp.

bool set_machine ( int32_t  num,
CMachine machine 
) [inherited]

set machine

Parameters:
num index of machine
machine machine to set
Returns:
if setting was successful

Definition at line 56 of file MulticlassMachine.h.

void set_max_iter ( int32_t  max_iter  ) 

set max iter

Parameters:
max_iter max iter value

Definition at line 76 of file MulticlassOCAS.h.

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_method ( int32_t  method  ) 

set method

Parameters:
method method value

Definition at line 89 of file MulticlassOCAS.h.

void set_rejection_strategy ( CRejectionStrategy rejection_strategy  )  [inherited]

sets rejection strategy

Parameters:
rejection_strategy rejection strategy to be set

Definition at line 130 of file MulticlassMachine.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.

virtual CSGObject* shallow_copy (  )  const [virtual, inherited]

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

Reimplemented in CGaussianKernel.

Definition at line 122 of file SGObject.h.

virtual void store_model_features (  )  [protected, virtual, inherited]

Stores feature data of underlying model. Does nothing because Linear machines store the normal vector of the separating hyperplane and therefore the model anyway

Reimplemented from CMachine.

Definition at line 162 of file LinearMulticlassMachine.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 machine

Reimplemented from CMulticlassMachine.

Definition at line 67 of file MulticlassOCAS.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.

int32_t m_buf_size [protected]

buffer size

Definition at line 157 of file MulticlassOCAS.h.

float64_t m_C [protected]

regularization constant for each machine

Definition at line 145 of file MulticlassOCAS.h.

bool m_data_locked [protected, inherited]

whether data is locked

Definition at line 365 of file Machine.h.

float64_t m_epsilon [protected]

tolerance

Definition at line 148 of file MulticlassOCAS.h.

CDotFeatures* m_features [protected, inherited]

features

Definition at line 167 of file LinearMulticlassMachine.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.

CMachine* m_machine [protected, inherited]

machine

Definition at line 191 of file MulticlassMachine.h.

CDynamicObjectArray* m_machines [protected, inherited]

machines

Definition at line 62 of file BaseMulticlassMachine.h.

int32_t m_max_iter [protected]

max number of iterations

Definition at line 151 of file MulticlassOCAS.h.

float64_t m_max_train_time [protected, inherited]

maximum training time

Definition at line 353 of file Machine.h.

int32_t m_method [protected]

method

Definition at line 154 of file MulticlassOCAS.h.

model selection parameters

Definition at line 474 of file SGObject.h.

CMulticlassStrategy* m_multiclass_strategy [protected, inherited]

type of multiclass strategy

Definition at line 188 of file MulticlassMachine.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.

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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