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CScatterSVM Class Reference

Detailed Description

ScatterSVM - Multiclass SVM.

The ScatterSVM is an unpublished experimental true multiclass SVM. Details are availabe in the following technical report.

This code is currently experimental.

Robert Jenssen and Marius Kloft and Alexander Zien and S"oren Sonnenburg and Klaus-Robert M"{u}ller, A Multi-Class Support Vector Machine Based on Scatter Criteria, TR 014-2009 TU Berlin, 2009

Definition at line 53 of file ScatterSVM.h.

Inheritance diagram for CScatterSVM:
Inheritance graph
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Public Member Functions

 CScatterSVM ()
 CScatterSVM (SCATTER_TYPE type)
 CScatterSVM (float64_t C, CKernel *k, CLabels *lab)
virtual ~CScatterSVM ()
virtual EMachineType get_classifier_type ()
virtual float64_t apply_one (int32_t num)
virtual CLabelsclassify_one_vs_rest ()
virtual const char * get_name () const
 MACHINE_PROBLEM_TYPE (PT_MULTICLASS)
bool create_multiclass_svm (int32_t num_classes)
bool set_svm (int32_t num, CSVM *svm)
CSVMget_svm (int32_t num)
bool load (FILE *svm_file)
bool save (FILE *svm_file)
SGVector< float64_tget_linear_term ()
float64_t get_tube_epsilon ()
float64_t get_epsilon ()
float64_t get_nu ()
float64_t get_C ()
int32_t get_qpsize ()
bool get_shrinking_enabled ()
float64_t get_objective ()
bool get_bias_enabled ()
bool get_linadd_enabled ()
bool get_batch_computation_enabled ()
void set_defaults (int32_t num_sv=0)
void set_linear_term (SGVector< float64_t > linear_term)
void set_C (float64_t C)
void set_epsilon (float64_t eps)
void set_nu (float64_t nue)
void set_tube_epsilon (float64_t eps)
void set_qpsize (int32_t qps)
void set_shrinking_enabled (bool enable)
void set_objective (float64_t v)
void set_bias_enabled (bool enable_bias)
void set_linadd_enabled (bool enable)
void set_batch_computation_enabled (bool enable)
void set_kernel (CKernel *k)
CKernelget_kernel ()
virtual void store_model_features ()
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 CMultilabelLabelsapply_multilabel_output (CFeatures *data=NULL, int32_t n_outputs=5)
CMulticlassStrategyget_multiclass_strategy () const
CRejectionStrategyget_rejection_strategy () const
void set_rejection_strategy (CRejectionStrategy *rejection_strategy)
EProbHeuristicType get_prob_heuris ()
void set_prob_heuris (EProbHeuristicType prob_heuris)
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 ()
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 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::get_version_parameter())
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_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_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
virtual void update_parameter_hash ()
virtual bool parameter_hash_changed ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
virtual CSGObjectclone ()

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

virtual bool train_machine (CFeatures *data=NULL)
CSVMsvm_proto ()
SGVector< int32_t > svm_svs ()
virtual bool init_machines_for_apply (CFeatures *data)
virtual bool is_acceptable_machine (CMachine *machine)
virtual bool init_machine_for_train (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 ()
void init_strategy ()
void clear_machines ()
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)

Protected Attributes

SCATTER_TYPE scatter_type
svm_problem problem
svm_parameter param
struct svm_model * model
float64_tnorm_wc
float64_tnorm_wcw
float64_t rho
int32_t m_num_classes
float64_t m_C
CKernelm_kernel
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

default constructor

Definition at line 24 of file ScatterSVM.cpp.

constructor

Definition at line 31 of file ScatterSVM.cpp.

CScatterSVM ( float64_t  C,
CKernel k,
CLabels lab 
)

constructor (using NO_BIAS as default scatter_type)

Parameters
Cconstant C
kkernel
lablabels

Definition at line 37 of file ScatterSVM.cpp.

~CScatterSVM ( )
virtual

default destructor

Definition at line 43 of file ScatterSVM.cpp.

Member Function Documentation

void add_machine_subset ( SGVector< index_t subset)
protectedvirtualinherited

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

Parameters
subsetsubset indices to set

Implements CMulticlassMachine.

Definition at line 178 of file KernelMulticlassMachine.cpp.

CLabels * apply ( CFeatures data = NULL)
virtualinherited

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 160 of file Machine.cpp.

CBinaryLabels * apply_binary ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of binary classification problem

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

Definition at line 216 of file Machine.cpp.

CLatentLabels * apply_latent ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of latent problem

Reimplemented in CLinearLatentMachine.

Definition at line 240 of file Machine.cpp.

CLabels * apply_locked ( SGVector< index_t indices)
virtualinherited

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

Parameters
indicesindex vector (of locked features) that is predicted

Definition at line 195 of file Machine.cpp.

CBinaryLabels * apply_locked_binary ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for binary problems

Reimplemented in CKernelMachine, and CMultitaskLinearMachine.

Definition at line 246 of file Machine.cpp.

CLatentLabels * apply_locked_latent ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for latent problems

Definition at line 274 of file Machine.cpp.

CMulticlassLabels * apply_locked_multiclass ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for multiclass problems

Definition at line 260 of file Machine.cpp.

CRegressionLabels * apply_locked_regression ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for regression problems

Reimplemented in CKernelMachine.

Definition at line 253 of file Machine.cpp.

CStructuredLabels * apply_locked_structured ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for structured problems

Definition at line 267 of file Machine.cpp.

CMulticlassLabels * apply_multiclass ( CFeatures data = NULL)
virtualinherited

classify all examples

Returns
resulting labels

Reimplemented from CMachine.

Reimplemented in CGaussianNaiveBayes, CMCLDA, and CQDA.

Definition at line 93 of file MulticlassMachine.cpp.

CMultilabelLabels * apply_multilabel_output ( CFeatures data = NULL,
int32_t  n_outputs = 5 
)
virtualinherited

classify all examples with multiple output

Returns
resulting labels

Definition at line 195 of file MulticlassMachine.cpp.

float64_t apply_one ( int32_t  num)
virtual

classify one example

Parameters
numnumber of example to classify
Returns
resulting classification

Reimplemented from CMulticlassMachine.

Definition at line 488 of file ScatterSVM.cpp.

CRegressionLabels * apply_regression ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of regression problem

Reimplemented in CKernelMachine, CWDSVMOcas, COnlineLinearMachine, CNeuralNetwork, CCHAIDTree, CStochasticGBMachine, CCARTree, CLinearMachine, CGaussianProcessRegression, and CBaggingMachine.

Definition at line 222 of file Machine.cpp.

CStructuredLabels * apply_structured ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of SO classification problem

Reimplemented in CLinearStructuredOutputMachine.

Definition at line 234 of file Machine.cpp.

void build_gradient_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
dictdictionary of parameters to be built.

Definition at line 1243 of file SGObject.cpp.

CLabels * classify_one_vs_rest ( )
virtual

classify one vs rest

Returns
resulting labels

Definition at line 378 of file ScatterSVM.cpp.

void clear_machines ( )
protectedinherited

clear machines

Reimplemented in CNativeMulticlassMachine.

CSGObject * clone ( )
virtualinherited

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.

Returns
an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

Definition at line 1360 of file SGObject.cpp.

bool create_multiclass_svm ( int32_t  num_classes)
inherited

create multiclass SVM. Appends the appropriate number of svm pointer (depending on multiclass strategy) to m_machines. All pointers are initialized with NULL.

Parameters
num_classesnumber of classes in SVM
Returns
if creation was successful

Definition at line 48 of file MulticlassSVM.cpp.

void data_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

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
labslabels used for locking
featuresfeatures used for locking

Reimplemented in CKernelMachine.

Definition at line 120 of file Machine.cpp.

void data_unlock ( )
virtualinherited

Unlocks a locked machine and restores previous state

Reimplemented in CKernelMachine.

Definition at line 151 of file Machine.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

A deep copy. All the instance variables will also be copied.

Definition at line 200 of file SGObject.cpp.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 
)
virtualinherited

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.

Parameters
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 1264 of file SGObject.cpp.

bool get_batch_computation_enabled ( )
inherited

get batch computation option of base SVM

Returns
whether batch computation of base SVM is enabled

Definition at line 146 of file MulticlassSVM.h.

bool get_bias_enabled ( )
inherited

get bias enabled options of base SVM

Returns
whether bias of base SVM is enabled

Definition at line 136 of file MulticlassSVM.h.

float64_t get_C ( )
inherited

get C of base SVM

Returns
C of base SVM

Definition at line 115 of file MulticlassSVM.h.

virtual EMachineType get_classifier_type ( )
virtual

get classifier type

Returns
classifier type LIBSVM

Reimplemented from CMachine.

Definition at line 77 of file ScatterSVM.h.

float64_t get_epsilon ( )
inherited

get epsilon of base SVM

Returns
epsilon of base SVM

Definition at line 105 of file MulticlassSVM.h.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 237 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 278 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 291 of file SGObject.cpp.

CKernel * get_kernel ( )
inherited

get kernel

Returns
kernel

Definition at line 122 of file KernelMulticlassMachine.cpp.

CLabels * get_labels ( )
virtualinherited

get labels

Returns
labels

Definition at line 84 of file Machine.cpp.

bool get_linadd_enabled ( )
inherited

get linadd option of base SVM

Returns
whether linadd of base SVM is enabled

Definition at line 141 of file MulticlassSVM.h.

SGVector<float64_t> get_linear_term ( )
inherited

get linear term of base SVM

Returns
linear term of base SVM

Definition at line 95 of file MulticlassSVM.h.

CMachine* get_machine ( int32_t  num) const
inherited

get machine

Parameters
numindex of machine to get
Returns
SVM at number num

Definition at line 74 of file MulticlassMachine.h.

CMachine * get_machine_from_trained ( CMachine machine)
protectedvirtualinherited

construct kernel machine from given kernel machine

Implements CMulticlassMachine.

Definition at line 168 of file KernelMulticlassMachine.cpp.

EProblemType get_machine_problem_type ( ) const
virtualinherited

get problem type

Reimplemented from CMachine.

Reimplemented in CCHAIDTree, and CCARTree.

Definition at line 32 of file BaseMulticlassMachine.cpp.

float64_t get_max_train_time ( )
inherited

get maximum training time

Returns
maximum training time

Definition at line 95 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 1135 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_namename of the parameter
Returns
description of the parameter

Definition at line 1159 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_namename of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1172 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 114 of file MulticlassMachine.h.

virtual const char* get_name ( ) const
virtual
Returns
object name

Reimplemented from CMulticlassSVM.

Definition at line 93 of file ScatterSVM.h.

float64_t get_nu ( )
inherited

get nu of base SVM

Returns
nu of base SVM

Definition at line 110 of file MulticlassSVM.h.

int32_t get_num_machines ( ) const
inherited

get number of machines

Returns
number of machines

Definition at line 27 of file BaseMulticlassMachine.cpp.

int32_t get_num_rhs_vectors ( )
protectedvirtualinherited

return number of rhs feature vectors

Implements CMulticlassMachine.

Definition at line 173 of file KernelMulticlassMachine.cpp.

float64_t get_objective ( )
inherited

get objective of base SVM

Returns
objective of base SVM

Definition at line 130 of file MulticlassSVM.h.

EProbHeuristicType get_prob_heuris ( )
inherited

get prob output heuristic of multiclass strategy

Definition at line 145 of file MulticlassMachine.h.

int32_t get_qpsize ( )
inherited

get qpsize of base SVM

Returns
qpsize of base SVM

Definition at line 120 of file MulticlassSVM.h.

CRejectionStrategy* get_rejection_strategy ( ) const
inherited

returns rejection strategy

Returns
rejection strategy

Definition at line 124 of file MulticlassMachine.h.

bool get_shrinking_enabled ( )
inherited

get shrinking option of base SVM

Returns
whether shrinking of base SVM is enabled

Definition at line 125 of file MulticlassSVM.h.

ESolverType get_solver_type ( )
inherited

get solver type

Returns
solver

Definition at line 110 of file Machine.cpp.

float64_t get_submachine_output ( int32_t  i,
int32_t  num 
)
virtualinherited

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

Parameters
inumber of submachine
numnumber of feature vector
Returns
output

Definition at line 80 of file MulticlassMachine.cpp.

CBinaryLabels * get_submachine_outputs ( int32_t  i)
virtualinherited

get outputs of i-th submachine

Parameters
inumber of submachine
Returns
outputs

Reimplemented in CDomainAdaptationMulticlassLibLinear.

Definition at line 71 of file MulticlassMachine.cpp.

CSVM* get_svm ( int32_t  num)
inherited

get SVM

Parameters
numwhich SVM to get
Returns
SVM at number num

Definition at line 76 of file MulticlassSVM.h.

float64_t get_tube_epsilon ( )
inherited

get tube epsilon of base SVM

Returns
tube epsilon of base SVM

Definition at line 100 of file MulticlassSVM.h.

bool init_machine_for_train ( CFeatures data)
protectedvirtualinherited

init machine for training with kernel init

Implements CMulticlassMachine.

Definition at line 128 of file KernelMulticlassMachine.cpp.

bool init_machines_for_apply ( CFeatures data)
protectedvirtualinherited

initializes machines (OvO, OvR) for apply

Reimplemented from CKernelMulticlassMachine.

Definition at line 73 of file MulticlassSVM.cpp.

void init_strategy ( )
protectedinherited

init strategy

Reimplemented in CNativeMulticlassMachine.

Definition at line 65 of file MulticlassMachine.cpp.

virtual bool is_acceptable_machine ( CMachine machine)
protectedvirtualinherited

is machine an SVM instance

Reimplemented from CMulticlassMachine.

Definition at line 232 of file MulticlassSVM.h.

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

Definition at line 294 of file Machine.h.

bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

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

Definition at line 297 of file SGObject.cpp.

bool is_label_valid ( CLabels lab) const
virtualinherited

check whether the labels is valid.

Parameters
labthe labels being checked, guaranteed to be non-NULL

Reimplemented from CMachine.

Reimplemented in CCARTree, and CCHAIDTree.

Definition at line 37 of file BaseMulticlassMachine.cpp.

bool is_ready ( )
protectedvirtualinherited

check kernel availability

Implements CMulticlassMachine.

Definition at line 160 of file KernelMulticlassMachine.cpp.

bool load ( FILE *  svm_file)
inherited

load a Multiclass SVM from file

Parameters
svm_filethe file handle

Definition at line 111 of file MulticlassSVM.cpp.

DynArray< TParameter * > * load_all_file_parameters ( int32_t  file_version,
int32_t  current_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

Parameters
file_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
Returns
(sorted) array of created TParameter instances with file data

Definition at line 704 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_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
Returns
new array with TParameter instances with the attached data

Definition at line 545 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

Parameters
filewhere to load from
prefixprefix 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

Definition at line 374 of file SGObject.cpp.

void load_serializable_post ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 1062 of file SGObject.cpp.

void load_serializable_pre ( ) throw (ShogunException)
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.

Exceptions
ShogunExceptionwill 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 1057 of file SGObject.cpp.

MACHINE_PROBLEM_TYPE ( PT_MULTICLASS  )
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_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

Definition at line 742 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
)
protectedvirtualinherited

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_baseset of TParameter instances to use for migration
targetparameter 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 949 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 
)
protectedvirtualinherited

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_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

Definition at line 889 of file SGObject.cpp.

bool parameter_hash_changed ( )
virtualinherited
Returns
whether parameter combination has changed since last update

Definition at line 263 of file SGObject.cpp.

virtual void post_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

post lock

Reimplemented in CMultitaskLinearMachine.

Definition at line 285 of file Machine.h.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1111 of file SGObject.cpp.

void print_serializable ( const char *  prefix = "")
virtualinherited

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 309 of file SGObject.cpp.

void remove_machine_subset ( )
protectedvirtualinherited

deletes any subset set to the features of the machine

Implements CMulticlassMachine.

Definition at line 183 of file KernelMulticlassMachine.cpp.

bool save ( FILE *  svm_file)
inherited

write a Multiclass SVM to a file

Parameters
svm_filethe file handle

Definition at line 259 of file MulticlassSVM.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Save this object to file.

Parameters
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix 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

Definition at line 315 of file SGObject.cpp.

void save_serializable_post ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 1072 of file SGObject.cpp.

void save_serializable_pre ( ) throw (ShogunException)
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.

Exceptions
ShogunExceptionwill 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 1067 of file SGObject.cpp.

void set_batch_computation_enabled ( bool  enable)
inherited

set batch computation option

Parameters
enablewhether batch computation should be enabled

Definition at line 207 of file MulticlassSVM.h.

void set_bias_enabled ( bool  enable_bias)
inherited

set bias option

Parameters
enable_biaswhether bias should be enabled

Definition at line 197 of file MulticlassSVM.h.

void set_C ( float64_t  C)
inherited

set C parameters

Parameters
Cset regularization parameter

Definition at line 162 of file MulticlassSVM.h.

void set_defaults ( int32_t  num_sv = 0)
inherited

set default number of support vectors

Parameters
num_svnumber of support vectors

Definition at line 152 of file MulticlassSVM.h.

void set_epsilon ( float64_t  eps)
inherited

set epsilon value

Parameters
epsepsilon value

Definition at line 167 of file MulticlassSVM.h.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 42 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 230 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 243 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 284 of file SGObject.cpp.

void set_kernel ( CKernel k)
inherited

set kernel

Parameters
kkernel

Definition at line 114 of file KernelMulticlassMachine.cpp.

void set_labels ( CLabels lab)
virtualinherited

set labels

Parameters
lablabels

Reimplemented from CMachine.

Definition at line 52 of file MulticlassMachine.cpp.

void set_linadd_enabled ( bool  enable)
inherited

set linadd option

Parameters
enablewhether linadd should be enabled

Definition at line 202 of file MulticlassSVM.h.

void set_linear_term ( SGVector< float64_t linear_term)
inherited

set linear term

Parameters
linear_termlinear term vector

Definition at line 157 of file MulticlassSVM.h.

bool set_machine ( int32_t  num,
CMachine machine 
)
inherited

set machine

Parameters
numindex of machine
machinemachine to set
Returns
if setting was successful

Definition at line 59 of file MulticlassMachine.h.

void set_max_train_time ( float64_t  t)
inherited

set maximum training time

Parameters
tmaximimum training time

Definition at line 90 of file Machine.cpp.

void set_nu ( float64_t  nue)
inherited

set nu value

Parameters
nuenu value

Definition at line 172 of file MulticlassSVM.h.

void set_objective ( float64_t  v)
inherited

set objective value

Parameters
vobjective value

Definition at line 192 of file MulticlassSVM.h.

void set_prob_heuris ( EProbHeuristicType  prob_heuris)
inherited

set prob output heuristic of multiclass strategy

Parameters
prob_heuristype of probability heuristic

Definition at line 153 of file MulticlassMachine.h.

void set_qpsize ( int32_t  qps)
inherited

set set QP size

Parameters
qpsqp size

Definition at line 182 of file MulticlassSVM.h.

void set_rejection_strategy ( CRejectionStrategy rejection_strategy)
inherited

sets rejection strategy

Parameters
rejection_strategyrejection strategy to be set

Definition at line 133 of file MulticlassMachine.h.

void set_shrinking_enabled ( bool  enable)
inherited

set shrinking option

Parameters
enablewhether shrinking should be enabled

Definition at line 187 of file MulticlassSVM.h.

void set_solver_type ( ESolverType  st)
inherited

set solver type

Parameters
stsolver type

Definition at line 105 of file Machine.cpp.

void set_store_model_features ( bool  store_model)
virtualinherited

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

Parameters
store_modelwhether model should be stored after training

Definition at line 115 of file Machine.cpp.

bool set_svm ( int32_t  num,
CSVM svm 
)
inherited

set SVM

Parameters
numnumber to set
svmSVM to set
Returns
if setting was successful

Definition at line 63 of file MulticlassSVM.cpp.

void set_tube_epsilon ( float64_t  eps)
inherited

set tube epsilon value

Parameters
epstube epsilon value

Definition at line 177 of file MulticlassSVM.h.

CSGObject * shallow_copy ( ) const
virtualinherited

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

Reimplemented in CGaussianKernel.

Definition at line 194 of file SGObject.cpp.

void store_model_features ( )
virtualinherited

Stores feature data of underlying model.

Need to store the SVs for all sub-machines. We make a union of the SVs for all sub-machines, store the union and adjust the sub-machines to index into the union.

Reimplemented from CMachine.

Definition at line 20 of file KernelMulticlassMachine.cpp.

virtual bool supports_locking ( ) const
virtualinherited
Returns
whether this machine supports locking

Reimplemented in CKernelMachine, and CMultitaskLinearMachine.

Definition at line 291 of file Machine.h.

CSVM* svm_proto ( )
protectedinherited

casts m_machine to SVM

Definition at line 218 of file MulticlassSVM.h.

SGVector<int32_t> svm_svs ( )
protectedinherited

returns support vectors

Definition at line 223 of file MulticlassSVM.h.

bool train ( CFeatures data = NULL)
virtualinherited

train machine

Parameters
datatraining 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 CRelaxedTree, CAutoencoder, CSGDQN, and COnlineSVMSGD.

Definition at line 47 of file Machine.cpp.

virtual bool train_locked ( SGVector< index_t indices)
virtualinherited

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

NOT IMPLEMENTED

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

Reimplemented in CKernelMachine, and CMultitaskLinearMachine.

Definition at line 237 of file Machine.h.

bool train_machine ( CFeatures data = NULL)
protectedvirtual

train SVM classifier

Parameters
datatraining data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data)
Returns
whether training was successful

Reimplemented from CMulticlassMachine.

Definition at line 49 of file ScatterSVM.cpp.

virtual bool train_require_labels ( ) const
protectedvirtualinherited

returns whether machine require labels for training

Reimplemented in COnlineLinearMachine, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree, and CLibSVMOneClass.

Definition at line 352 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 304 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 250 of file SGObject.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 496 of file SGObject.h.

float64_t m_C
protectedinherited

C regularization constant

Definition at line 247 of file MulticlassSVM.h.

bool m_data_locked
protectedinherited

whether data is locked

Definition at line 368 of file Machine.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 511 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 517 of file SGObject.h.

CKernel* m_kernel
protectedinherited

kernel

Definition at line 100 of file KernelMulticlassMachine.h.

CLabels* m_labels
protectedinherited

labels

Definition at line 359 of file Machine.h.

CMachine* m_machine
protectedinherited

machine

Definition at line 208 of file MulticlassMachine.h.

CDynamicObjectArray* m_machines
protectedinherited

machines

Definition at line 56 of file BaseMulticlassMachine.h.

float64_t m_max_train_time
protectedinherited

maximum training time

Definition at line 356 of file Machine.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 508 of file SGObject.h.

CMulticlassStrategy* m_multiclass_strategy
protectedinherited

type of multiclass strategy

Definition at line 205 of file MulticlassMachine.h.

int32_t m_num_classes
protected

number of classes

Definition at line 136 of file ScatterSVM.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 514 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 505 of file SGObject.h.

ESolverType m_solver_type
protectedinherited

solver type

Definition at line 362 of file Machine.h.

bool m_store_model_features
protectedinherited

whether model features should be stored after training

Definition at line 365 of file Machine.h.

struct svm_model* model
protected

SVM model

Definition at line 124 of file ScatterSVM.h.

float64_t* norm_wc
protected

norm of w_c

Definition at line 127 of file ScatterSVM.h.

float64_t* norm_wcw
protected

norm of w_cw

Definition at line 130 of file ScatterSVM.h.

Parallel* parallel
inherited

parallel

Definition at line 499 of file SGObject.h.

svm_parameter param
protected

SVM param

Definition at line 121 of file ScatterSVM.h.

svm_problem problem
protected

SVM problem

Definition at line 119 of file ScatterSVM.h.

float64_t rho
protected

ScatterSVM rho

Definition at line 133 of file ScatterSVM.h.

SCATTER_TYPE scatter_type
protected

type of scatter SVM

Definition at line 116 of file ScatterSVM.h.

Version* version
inherited

version

Definition at line 502 of file SGObject.h.


The documentation for this class was generated from the following files:

SHOGUN Machine Learning Toolbox - Documentation