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CSVMLight Class Reference

Detailed Description

class SVMlight

Definition at line 225 of file SVMLight.h.

Inheritance diagram for CSVMLight:
Inheritance graph
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Public Member Functions

 CSVMLight ()
 CSVMLight (float64_t C, CKernel *k, CLabels *lab)
virtual ~CSVMLight ()
void init ()
virtual EMachineType get_classifier_type ()
int32_t get_runtime ()
void svm_learn ()
int32_t optimize_to_convergence (int32_t *docs, int32_t *label, int32_t totdoc, SHRINK_STATE *shrink_state, int32_t *inconsistent, float64_t *a, float64_t *lin, float64_t *c, TIMING *timing_profile, float64_t *maxdiff, int32_t heldout, int32_t retrain)
virtual float64_t compute_objective_function (float64_t *a, float64_t *lin, float64_t *c, float64_t *eps, int32_t *label, int32_t totdoc)
void clear_index (int32_t *index)
void add_to_index (int32_t *index, int32_t elem)
int32_t compute_index (int32_t *binfeature, int32_t range, int32_t *index)
void optimize_svm (int32_t *docs, int32_t *label, int32_t *exclude_from_eq_const, float64_t eq_target, int32_t *chosen, int32_t *active2dnum, int32_t totdoc, int32_t *working2dnum, int32_t varnum, float64_t *a, float64_t *lin, float64_t *c, float64_t *aicache, QP *qp, float64_t *epsilon_crit_target)
void compute_matrices_for_optimization (int32_t *docs, int32_t *label, int32_t *exclude_from_eq_const, float64_t eq_target, int32_t *chosen, int32_t *active2dnum, int32_t *key, float64_t *a, float64_t *lin, float64_t *c, int32_t varnum, int32_t totdoc, float64_t *aicache, QP *qp)
void compute_matrices_for_optimization_parallel (int32_t *docs, int32_t *label, int32_t *exclude_from_eq_const, float64_t eq_target, int32_t *chosen, int32_t *active2dnum, int32_t *key, float64_t *a, float64_t *lin, float64_t *c, int32_t varnum, int32_t totdoc, float64_t *aicache, QP *qp)
int32_t calculate_svm_model (int32_t *docs, int32_t *label, float64_t *lin, float64_t *a, float64_t *a_old, float64_t *c, int32_t *working2dnum, int32_t *active2dnum)
int32_t check_optimality (int32_t *label, float64_t *a, float64_t *lin, float64_t *c, int32_t totdoc, float64_t *maxdiff, float64_t epsilon_crit_org, int32_t *misclassified, int32_t *inconsistent, int32_t *active2dnum, int32_t *last_suboptimal_at, int32_t iteration)
virtual void update_linear_component (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache, float64_t *c)
void update_linear_component_mkl (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache)
void update_linear_component_mkl_linadd (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache)
void call_mkl_callback (float64_t *a, int32_t *label, float64_t *lin)
int32_t select_next_qp_subproblem_grad (int32_t *label, float64_t *a, float64_t *lin, float64_t *c, int32_t totdoc, int32_t qp_size, int32_t *inconsistent, int32_t *active2dnum, int32_t *working2dnum, float64_t *selcrit, int32_t *select, int32_t cache_only, int32_t *key, int32_t *chosen)
int32_t select_next_qp_subproblem_rand (int32_t *label, float64_t *a, float64_t *lin, float64_t *c, int32_t totdoc, int32_t qp_size, int32_t *inconsistent, int32_t *active2dnum, int32_t *working2dnum, float64_t *selcrit, int32_t *select, int32_t *key, int32_t *chosen, int32_t iteration)
void select_top_n (float64_t *selcrit, int32_t range, int32_t *select, int32_t n)
void init_shrink_state (SHRINK_STATE *shrink_state, int32_t totdoc, int32_t maxhistory)
void shrink_state_cleanup (SHRINK_STATE *shrink_state)
int32_t shrink_problem (SHRINK_STATE *shrink_state, int32_t *active2dnum, int32_t *last_suboptimal_at, int32_t iteration, int32_t totdoc, int32_t minshrink, float64_t *a, int32_t *inconsistent, float64_t *c, float64_t *lin, int *label)
virtual void reactivate_inactive_examples (int32_t *label, float64_t *a, SHRINK_STATE *shrink_state, float64_t *lin, float64_t *c, int32_t totdoc, int32_t iteration, int32_t *inconsistent, int32_t *docs, float64_t *aicache, float64_t *maxdiff)
 MACHINE_PROBLEM_TYPE (PT_BINARY)
void set_defaults (int32_t num_sv=0)
virtual SGVector< float64_tget_linear_term ()
virtual void set_linear_term (const SGVector< float64_t > linear_term)
bool load (FILE *svm_file)
bool save (FILE *svm_file)
void set_nu (float64_t nue)
void set_C (float64_t c_neg, float64_t c_pos)
void set_epsilon (float64_t eps)
void set_tube_epsilon (float64_t eps)
float64_t get_tube_epsilon ()
void set_qpsize (int32_t qps)
float64_t get_epsilon ()
float64_t get_nu ()
float64_t get_C1 ()
float64_t get_C2 ()
int32_t get_qpsize ()
void set_shrinking_enabled (bool enable)
bool get_shrinking_enabled ()
float64_t compute_svm_dual_objective ()
float64_t compute_svm_primal_objective ()
void set_objective (float64_t v)
float64_t get_objective ()
void set_callback_function (CMKL *m, bool(*cb)(CMKL *mkl, const float64_t *sumw, const float64_t suma))
void set_kernel (CKernel *k)
CKernelget_kernel ()
void set_batch_computation_enabled (bool enable)
bool get_batch_computation_enabled ()
void set_linadd_enabled (bool enable)
bool get_linadd_enabled ()
void set_bias_enabled (bool enable_bias)
bool get_bias_enabled ()
float64_t get_bias ()
void set_bias (float64_t bias)
int32_t get_support_vector (int32_t idx)
float64_t get_alpha (int32_t idx)
bool set_support_vector (int32_t idx, int32_t val)
bool set_alpha (int32_t idx, float64_t val)
int32_t get_num_support_vectors ()
void set_alphas (SGVector< float64_t > alphas)
void set_support_vectors (SGVector< int32_t > svs)
SGVector< int32_t > get_support_vectors ()
SGVector< float64_tget_alphas ()
bool create_new_model (int32_t num)
bool init_kernel_optimization ()
virtual CRegressionLabelsapply_regression (CFeatures *data=NULL)
virtual CBinaryLabelsapply_binary (CFeatures *data=NULL)
virtual float64_t apply_one (int32_t num)
virtual bool train_locked (SGVector< index_t > indices)
virtual CBinaryLabelsapply_locked_binary (SGVector< index_t > indices)
virtual CRegressionLabelsapply_locked_regression (SGVector< index_t > indices)
virtual SGVector< float64_tapply_locked_get_output (SGVector< index_t > indices)
virtual void data_lock (CLabels *labs, CFeatures *features=NULL)
virtual void data_unlock ()
virtual bool supports_locking () const
virtual bool train (CFeatures *data=NULL)
virtual CLabelsapply (CFeatures *data=NULL)
virtual CMulticlassLabelsapply_multiclass (CFeatures *data=NULL)
virtual CStructuredLabelsapply_structured (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 ()
void set_solver_type (ESolverType st)
ESolverType get_solver_type ()
virtual void set_store_model_features (bool store_model)
virtual CLabelsapply_locked (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 post_lock (CLabels *labs, CFeatures *features)
bool is_data_locked () const
virtual EProblemType get_machine_problem_type () 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 ()

Static Public Member Functions

static void * update_linear_component_mkl_linadd_helper (void *p)
static void * apply_helper (void *p)

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 float64_t compute_kernel (int32_t i, int32_t j)
virtual const char * get_name () const
float64_toptimize_qp (QP *qp, float64_t *epsilon_crit, int32_t nx, float64_t *threshold, int32_t &svm_maxqpsize)
virtual bool train_machine (CFeatures *data=NULL)
virtual float64_tget_linear_term_array ()
SGVector< float64_tapply_get_outputs (CFeatures *data)
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)

Static Protected Member Functions

static void * compute_kernel_helper (void *p)
static void * update_linear_component_linadd_helper (void *p)
static void * reactivate_inactive_examples_vanilla_helper (void *p)
static void * reactivate_inactive_examples_linadd_helper (void *p)

Protected Attributes

MODEL * model
LEARN_PARM * learn_parm
int32_t verbosity
float64_t init_margin
int32_t init_iter
int32_t precision_violations
float64_t model_b
float64_t opt_precision
float64_tprimal
float64_tdual
float64_tW
int32_t count
float64_t mymaxdiff
bool use_kernel_cache
bool mkl_converged
SGVector< float64_tm_linear_term
bool svm_loaded
float64_t epsilon
float64_t tube_epsilon
float64_t nu
float64_t C1
float64_t C2
float64_t objective
int32_t qpsize
bool use_shrinking
bool(* callback )(CMKL *mkl, const float64_t *sumw, const float64_t suma)
CMKLmkl
CKernelkernel
CCustomKernelm_custom_kernel
CKernelm_kernel_backup
bool use_batch_computation
bool use_linadd
bool use_bias
float64_t m_bias
SGVector< float64_tm_alpha
SGVector< int32_t > m_svs
float64_t m_max_train_time
CLabelsm_labels
ESolverType m_solver_type
bool m_store_model_features
bool m_data_locked

Constructor & Destructor Documentation

CSVMLight ( )

default constructor

Definition at line 126 of file SVMLight.cpp.

CSVMLight ( float64_t  C,
CKernel k,
CLabels lab 
)

constructor

Parameters
Cconstant C
kkernel
lablabels

Definition at line 133 of file SVMLight.cpp.

~CSVMLight ( )
virtual

Definition at line 164 of file SVMLight.cpp.

Member Function Documentation

void add_to_index ( int32_t *  index,
int32_t  elem 
)

add to index

Parameters
indexindex
elemelement at index

Definition at line 978 of file SVMLight.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 kernel machine to data for binary classification task

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

Reimplemented from CMachine.

Reimplemented in CDomainAdaptationSVM.

Definition at line 249 of file KernelMachine.cpp.

SGVector< float64_t > apply_get_outputs ( CFeatures data)
protectedinherited

apply get outputs

Parameters
datafeatures to compute outputs
Returns
outputs

Definition at line 255 of file KernelMachine.cpp.

void * apply_helper ( void *  p)
staticinherited

apply example helper, used in threads

Parameters
pparams of the thread
Returns
nothing really

Definition at line 425 of file KernelMachine.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. Error if machine is not locked. Binary case

Parameters
indicesindex vector (of locked features) that is predicted
Returns
resulting labels

Reimplemented from CMachine.

Definition at line 519 of file KernelMachine.cpp.

SGVector< float64_t > apply_locked_get_output ( 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
Returns
raw output of machine

Definition at line 532 of file KernelMachine.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. Error if machine is not locked. Binary case

Parameters
indicesindex vector (of locked features) that is predicted
Returns
resulting labels

Reimplemented from CMachine.

Definition at line 525 of file KernelMachine.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
float64_t apply_one ( int32_t  num)
virtualinherited

apply kernel machine to one example

Parameters
numwhich example to apply to
Returns
classified value

Reimplemented from CMachine.

Definition at line 406 of file KernelMachine.cpp.

CRegressionLabels * apply_regression ( CFeatures data = NULL)
virtualinherited

apply kernel machine to data for regression task

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

Reimplemented from CMachine.

Definition at line 243 of file KernelMachine.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.

int32_t calculate_svm_model ( int32_t *  docs,
int32_t *  label,
float64_t lin,
float64_t a,
float64_t a_old,
float64_t c,
int32_t *  working2dnum,
int32_t *  active2dnum 
)

calculate SVM model

Parameters
docsdocs
labellabel
linlin
aa
a_oldold a
cc
working2dnumworking 2D num
active2dnumactive 2D num
Returns
something inty

Definition at line 1249 of file SVMLight.cpp.

void call_mkl_callback ( float64_t a,
int32_t *  label,
float64_t lin 
)

Definition at line 1685 of file SVMLight.cpp.

int32_t check_optimality ( int32_t *  label,
float64_t a,
float64_t lin,
float64_t c,
int32_t  totdoc,
float64_t maxdiff,
float64_t  epsilon_crit_org,
int32_t *  misclassified,
int32_t *  inconsistent,
int32_t *  active2dnum,
int32_t *  last_suboptimal_at,
int32_t  iteration 
)

check optimality

Parameters
labellabel
aa
linlin
cc
totdoctotdoc
maxdiffmaximum diff
epsilon_crit_orgepsilon crit org
misclassifiedmisclassified
inconsistentinconsistent
active2dnumactive 2D num
last_suboptimal_atlast suboptimal at
iterationiteration
Returns
something inty

Definition at line 1366 of file SVMLight.cpp.

void clear_index ( int32_t *  index)

clear index

Parameters
indexindex

Definition at line 972 of file SVMLight.cpp.

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.

int32_t compute_index ( int32_t *  binfeature,
int32_t  range,
int32_t *  index 
)

compute index

Parameters
binfeaturebinary feature
rangerange
index
Returns
something inty

Definition at line 987 of file SVMLight.cpp.

virtual float64_t compute_kernel ( int32_t  i,
int32_t  j 
)
protectedvirtual

compute kernel

Parameters
iat index i
jat index j
Returns
computed kernel item at index i, j

Reimplemented in CSVRLight.

Definition at line 605 of file SVMLight.h.

void * compute_kernel_helper ( void *  p)
staticprotected

helper for compute kernel

Parameters
pp

Definition at line 115 of file SVMLight.cpp.

void compute_matrices_for_optimization ( int32_t *  docs,
int32_t *  label,
int32_t *  exclude_from_eq_const,
float64_t  eq_target,
int32_t *  chosen,
int32_t *  active2dnum,
int32_t *  key,
float64_t a,
float64_t lin,
float64_t c,
int32_t  varnum,
int32_t  totdoc,
float64_t aicache,
QP *  qp 
)

compute matrices for optimization

Parameters
docsdocs
labellabel
exclude_from_eq_constexclude from eq const
eq_targeteq target
chosenchosen
active2dnumactive 2D num
keykey
aa
linlin
cc
varnumvar num
totdoctotdoc
aicacheai cache
qpQP

Definition at line 1176 of file SVMLight.cpp.

void compute_matrices_for_optimization_parallel ( int32_t *  docs,
int32_t *  label,
int32_t *  exclude_from_eq_const,
float64_t  eq_target,
int32_t *  chosen,
int32_t *  active2dnum,
int32_t *  key,
float64_t a,
float64_t lin,
float64_t c,
int32_t  varnum,
int32_t  totdoc,
float64_t aicache,
QP *  qp 
)

compute matrices for optimization in parallel

Parameters
docsdocs
labellabel
exclude_from_eq_constexclude from eq const
eq_targeteq target
chosenchosen
active2dnumactive 2D num
keykey
aa
linlin
cc
varnumvar num
totdoctotdoc
aicacheai cache
qpQP

Definition at line 1044 of file SVMLight.cpp.

float64_t compute_objective_function ( float64_t a,
float64_t lin,
float64_t c,
float64_t eps,
int32_t *  label,
int32_t  totdoc 
)
virtual

compute objective function

Parameters
aa
linlin
cc
epsepsilon
labellabel
totdoctotdoc
Returns
something floaty

Reimplemented in CSVRLight.

Definition at line 956 of file SVMLight.cpp.

float64_t compute_svm_dual_objective ( )
inherited

compute svm dual objective

Returns
computed dual objective

Definition at line 242 of file SVM.cpp.

float64_t compute_svm_primal_objective ( )
inherited

compute svm primal objective

Returns
computed svm primal objective

Definition at line 267 of file SVM.cpp.

bool create_new_model ( int32_t  num)
inherited

create new model

Parameters
numnumber of alphas and support vectors in new model

Definition at line 195 of file KernelMachine.cpp.

void data_lock ( CLabels labs,
CFeatures features = NULL 
)
virtualinherited

Locks the machine on given labels and data. After this call, only train_locked and apply_locked may be called.

Computes kernel matrix to speed up train/apply calls

Parameters
labslabels used for locking
featuresfeatures used for locking

Reimplemented from CMachine.

Definition at line 624 of file KernelMachine.cpp.

void data_unlock ( )
virtualinherited

Unlocks a locked machine and restores previous state

Reimplemented from CMachine.

Definition at line 655 of file KernelMachine.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.

float64_t get_alpha ( int32_t  idx)
inherited

get alpha at given index

Parameters
idxindex of alpha
Returns
alpha

Definition at line 141 of file KernelMachine.cpp.

SGVector< float64_t > get_alphas ( )
inherited
Returns
vector of alphas

Definition at line 190 of file KernelMachine.cpp.

bool get_batch_computation_enabled ( )
inherited

check if batch computation is enabled

Returns
if batch computation is enabled

Definition at line 100 of file KernelMachine.cpp.

float64_t get_bias ( )
inherited

get bias

Returns
bias

Definition at line 125 of file KernelMachine.cpp.

bool get_bias_enabled ( )
inherited

get state of bias

Returns
state of bias

Definition at line 120 of file KernelMachine.cpp.

float64_t get_C1 ( )
inherited

get C1

Returns
C1

Definition at line 161 of file SVM.h.

float64_t get_C2 ( )
inherited

get C2

Returns
C2

Definition at line 167 of file SVM.h.

virtual EMachineType get_classifier_type ( )
virtual

get classifier type

Returns
classifier type LIGHT

Reimplemented from CMachine.

Reimplemented in CSVRLight, CDomainAdaptationSVM, and CSVMLightOneClass.

Definition at line 247 of file SVMLight.h.

float64_t get_epsilon ( )
inherited

get epsilon

Returns
epsilon

Definition at line 149 of file SVM.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 89 of file KernelMachine.cpp.

CLabels * get_labels ( )
virtualinherited

get labels

Returns
labels

Definition at line 84 of file Machine.cpp.

bool get_linadd_enabled ( )
inherited

check if linadd is enabled

Returns
if linadd is enabled

Definition at line 110 of file KernelMachine.cpp.

SGVector< float64_t > get_linear_term ( )
virtualinherited

get linear term

Returns
the linear term

Definition at line 332 of file SVM.cpp.

float64_t * get_linear_term_array ( )
protectedvirtualinherited

get linear term copy as dynamic array

Returns
linear term copied to a dynamic array

Definition at line 302 of file SVM.cpp.

virtual EProblemType get_machine_problem_type ( ) const
virtualinherited

returns type of problem machine solves

Reimplemented in CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree, and CBaseMulticlassMachine.

Definition at line 297 of file Machine.h.

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.

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

Reimplemented from CSVM.

Reimplemented in CSVRLight, CDomainAdaptationSVM, and CSVMLightOneClass.

Definition at line 635 of file SVMLight.h.

float64_t get_nu ( )
inherited

get nu

Returns
nu

Definition at line 155 of file SVM.h.

int32_t get_num_support_vectors ( )
inherited

get number of support vectors

Returns
number of support vectors

Definition at line 170 of file KernelMachine.cpp.

float64_t get_objective ( )
inherited

get objective

Returns
objective

Definition at line 218 of file SVM.h.

int32_t get_qpsize ( )
inherited

get qpsize

Returns
qpsize

Definition at line 173 of file SVM.h.

int32_t get_runtime ( )

get runtime

Returns
runtime

Definition at line 293 of file SVMLight.cpp.

bool get_shrinking_enabled ( )
inherited

get state of shrinking

Returns
if shrinking is enabled

Definition at line 188 of file SVM.h.

ESolverType get_solver_type ( )
inherited

get solver type

Returns
solver

Definition at line 110 of file Machine.cpp.

int32_t get_support_vector ( int32_t  idx)
inherited

get support vector at given index

Parameters
idxindex of support vector
Returns
support vector

Definition at line 135 of file KernelMachine.cpp.

SGVector< int32_t > get_support_vectors ( )
inherited
Returns
all support vectors

Definition at line 185 of file KernelMachine.cpp.

float64_t get_tube_epsilon ( )
inherited

get tube epsilon

Returns
tube epsilon

Definition at line 137 of file SVM.h.

void init ( )

init SVM

Reimplemented from CKernelMachine.

Definition at line 139 of file SVMLight.cpp.

bool init_kernel_optimization ( )
inherited

initialise kernel optimisation

Returns
if operation was successful

Definition at line 212 of file KernelMachine.cpp.

void init_shrink_state ( SHRINK_STATE *  shrink_state,
int32_t  totdoc,
int32_t  maxhistory 
)

init shrink state

Parameters
shrink_stateshrink state
totdoctotdoc
maxhistorymaximum history

Definition at line 1944 of file SVMLight.cpp.

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.

virtual bool is_label_valid ( CLabels lab) const
protectedvirtualinherited

check whether the labels is valid.

Subclasses can override this to implement their check of label types.

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

Reimplemented in CNeuralNetwork, CCARTree, CCHAIDTree, CGaussianProcessRegression, and CBaseMulticlassMachine.

Definition at line 346 of file Machine.h.

bool load ( FILE *  svm_file)
inherited

load a SVM from file

Parameters
svm_filethe file handle

Definition at line 90 of file SVM.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_BINARY  )
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.

float64_t * optimize_qp ( QP *  qp,
float64_t epsilon_crit,
int32_t  nx,
float64_t threshold,
int32_t &  svm_maxqpsize 
)
protected

Definition at line 2396 of file SVMLight.cpp.

void optimize_svm ( int32_t *  docs,
int32_t *  label,
int32_t *  exclude_from_eq_const,
float64_t  eq_target,
int32_t *  chosen,
int32_t *  active2dnum,
int32_t  totdoc,
int32_t *  working2dnum,
int32_t  varnum,
float64_t a,
float64_t lin,
float64_t c,
float64_t aicache,
QP *  qp,
float64_t epsilon_crit_target 
)

optimise SVM

Parameters
docsdocs
labellabel
exclude_from_eq_constexclude from eq const
eq_targeteq target
chosenchosen
active2dnumactive 2D num
totdoctotdoc
working2dnumworking 2D num
varnumvar num
aa
linlin
cc
aicacheai cache
qpQP
epsilon_crit_targetepsilon crit target

Definition at line 1007 of file SVMLight.cpp.

int32_t optimize_to_convergence ( int32_t *  docs,
int32_t *  label,
int32_t  totdoc,
SHRINK_STATE *  shrink_state,
int32_t *  inconsistent,
float64_t a,
float64_t lin,
float64_t c,
TIMING *  timing_profile,
float64_t maxdiff,
int32_t  heldout,
int32_t  retrain 
)

optimize to convergence

Parameters
docsthe docs
labelthe label
totdocthe totdoc
shrink_stateshrink state
inconsistentinconsistent
aa
linlin
cc
timing_profiletiming profile
maxdiffmaximum diff
heldoutheld out
retrainretrain
Returns
something inty

Definition at line 546 of file SVMLight.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 reactivate_inactive_examples ( int32_t *  label,
float64_t a,
SHRINK_STATE *  shrink_state,
float64_t lin,
float64_t c,
int32_t  totdoc,
int32_t  iteration,
int32_t *  inconsistent,
int32_t *  docs,
float64_t aicache,
float64_t maxdiff 
)
virtual

reactivate inactive examples

Parameters
labellabel
aa
shrink_stateshrink state
linlin
cc
totdoctotdoc
iterationiteration
inconsistentinconsistent
docsdocs
aicacheai cache
maxdiffmaximum diff

Reimplemented in CSVRLight.

Definition at line 2097 of file SVMLight.cpp.

void * reactivate_inactive_examples_linadd_helper ( void *  p)
staticprotected

helper for reactivate inactive examples linadd

Parameters
pp

Definition at line 2037 of file SVMLight.cpp.

void * reactivate_inactive_examples_vanilla_helper ( void *  p)
staticprotected

helper for reactivate inactive examples vanilla

Parameters
pp

Definition at line 2060 of file SVMLight.cpp.

bool save ( FILE *  svm_file)
inherited

write a SVM to a file

Parameters
svm_filethe file handle

Definition at line 206 of file SVM.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.

int32_t select_next_qp_subproblem_grad ( int32_t *  label,
float64_t a,
float64_t lin,
float64_t c,
int32_t  totdoc,
int32_t  qp_size,
int32_t *  inconsistent,
int32_t *  active2dnum,
int32_t *  working2dnum,
float64_t selcrit,
int32_t *  select,
int32_t  cache_only,
int32_t *  key,
int32_t *  chosen 
)

select next qp subproblem grad

Parameters
labellabel
aa
linlin
cc
totdoctotdoc
qp_sizesize of qp
inconsistentinconsistent
active2dnumactive 2D num
working2dnumworking 2D num
selcritselcrit
selectselect
cache_onlycache only
keykey
chosenchosen
Returns
something inty

Definition at line 1746 of file SVMLight.cpp.

int32_t select_next_qp_subproblem_rand ( int32_t *  label,
float64_t a,
float64_t lin,
float64_t c,
int32_t  totdoc,
int32_t  qp_size,
int32_t *  inconsistent,
int32_t *  active2dnum,
int32_t *  working2dnum,
float64_t selcrit,
int32_t *  select,
int32_t *  key,
int32_t *  chosen,
int32_t  iteration 
)

select next qp subproblem rand

Parameters
labellabel
aa
linlin
cc
totdoctotdoc
qp_sizesize of qp
inconsistentinconsistent
active2dnumactive 2D num
working2dnumworking 2D num
selcritselcrit
selectselect
keykey
chosenchosen
iterationiteration
Returns
something inty

Definition at line 1838 of file SVMLight.cpp.

void select_top_n ( float64_t selcrit,
int32_t  range,
int32_t *  select,
int32_t  n 
)

select top n

Parameters
selcritselcrit
rangerange
selectselect
nn

Definition at line 1908 of file SVMLight.cpp.

bool set_alpha ( int32_t  idx,
float64_t  val 
)
inherited

set alpha at given index to given value

Parameters
idxindex of alpha vector
valnew value of alpha vector
Returns
if operation was successful

Definition at line 160 of file KernelMachine.cpp.

void set_alphas ( SGVector< float64_t alphas)
inherited

set alphas to given values

Parameters
alphasfloat vector with all alphas to set

Definition at line 175 of file KernelMachine.cpp.

void set_batch_computation_enabled ( bool  enable)
inherited

set batch computation enabled

Parameters
enableif batch computation shall be enabled

Definition at line 95 of file KernelMachine.cpp.

void set_bias ( float64_t  bias)
inherited

set bias to given value

Parameters
biasnew bias

Definition at line 130 of file KernelMachine.cpp.

void set_bias_enabled ( bool  enable_bias)
inherited

set state of bias

Parameters
enable_biasif bias shall be enabled

Definition at line 115 of file KernelMachine.cpp.

void set_C ( float64_t  c_neg,
float64_t  c_pos 
)
inherited

set C

Parameters
c_negnew C constant for negatively labeled examples
c_posnew C constant for positively labeled examples

Note that not all SVMs support this (however at least CLibSVM and CSVMLight do)

Definition at line 118 of file SVM.h.

void set_callback_function ( CMKL m,
bool(*)(CMKL *mkl, const float64_t *sumw, const float64_t suma)  cb 
)
inherited

set callback function svm optimizers may call when they have a new (small) set of alphas

Parameters
mpointer to mkl object
cbcallback function

Definition at line 232 of file SVM.cpp.

void set_defaults ( int32_t  num_sv = 0)
inherited

set default values for members a SVM object

Definition at line 48 of file SVM.cpp.

void set_epsilon ( float64_t  eps)
inherited

set epsilon

Parameters
epsnew epsilon

Definition at line 125 of file SVM.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 82 of file KernelMachine.cpp.

void set_labels ( CLabels lab)
virtualinherited

set labels

Parameters
lablabels

Reimplemented in CNeuralNetwork, CGaussianProcessMachine, CCARTree, CStructuredOutputMachine, CRelaxedTree, and CMulticlassMachine.

Definition at line 73 of file Machine.cpp.

void set_linadd_enabled ( bool  enable)
inherited

set linadd enabled

Parameters
enableif linadd shall be enabled

Definition at line 105 of file KernelMachine.cpp.

void set_linear_term ( const SGVector< float64_t linear_term)
virtualinherited

set linear term of the QP

Parameters
linear_termthe linear term

Definition at line 314 of file SVM.cpp.

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

Parameters
nuenew nu

Definition at line 107 of file SVM.h.

void set_objective ( float64_t  v)
inherited

set objective

Parameters
vobjective

Definition at line 209 of file SVM.h.

void set_qpsize ( int32_t  qps)
inherited

set qpsize

Parameters
qpsnew qpsize

Definition at line 143 of file SVM.h.

void set_shrinking_enabled ( bool  enable)
inherited

set state of shrinking

Parameters
enableif shrinking will be enabled

Definition at line 179 of file SVM.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_support_vector ( int32_t  idx,
int32_t  val 
)
inherited

set support vector at given index to given value

Parameters
idxindex of support vector
valnew value of support vector
Returns
if operation was successful

Definition at line 150 of file KernelMachine.cpp.

void set_support_vectors ( SGVector< int32_t >  svs)
inherited

set support vectors to given values

Parameters
svsinteger vector with all support vectors indexes to set

Definition at line 180 of file KernelMachine.cpp.

void set_tube_epsilon ( float64_t  eps)
inherited

set tube epsilon

Parameters
epsnew tube epsilon

Definition at line 131 of file SVM.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.

int32_t shrink_problem ( SHRINK_STATE *  shrink_state,
int32_t *  active2dnum,
int32_t *  last_suboptimal_at,
int32_t  iteration,
int32_t  totdoc,
int32_t  minshrink,
float64_t a,
int32_t *  inconsistent,
float64_t c,
float64_t lin,
int *  label 
)

shrink problem

Parameters
shrink_stateshrink state
active2dnumactive 2D num
last_suboptimal_atlast suboptimal at
iterationiteration
totdoctotdoc
minshrinkminimal shrink
aa
inconsistentinconsistent
cc
linlin
labellabel
Returns
something inty

Definition at line 1976 of file SVMLight.cpp.

void shrink_state_cleanup ( SHRINK_STATE *  shrink_state)

cleanup shrink state

Parameters
shrink_stateshrink state

Definition at line 1965 of file SVMLight.cpp.

void store_model_features ( )
protectedvirtualinherited

Stores feature data of the SV indices and sets it to the lhs of the underlying kernel. Then, all SV indices are set to identity.

May be overwritten by subclasses in case the model should be stored differently.

Reimplemented from CMachine.

Definition at line 454 of file KernelMachine.cpp.

bool supports_locking ( ) const
virtualinherited
Returns
whether machine supports locking

Reimplemented from CMachine.

Definition at line 713 of file KernelMachine.cpp.

void svm_learn ( )

learn SVM

Definition at line 301 of file SVMLight.cpp.

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.

bool train_locked ( SGVector< index_t indices)
virtualinherited

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

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

Reimplemented from CMachine.

Definition at line 483 of file KernelMachine.cpp.

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 CMachine.

Reimplemented in CSVRLight, CDomainAdaptationSVM, and CSVMLightOneClass.

Definition at line 181 of file SVMLight.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_linear_component ( int32_t *  docs,
int32_t *  label,
int32_t *  active2dnum,
float64_t a,
float64_t a_old,
int32_t *  working2dnum,
int32_t  totdoc,
float64_t lin,
float64_t aicache,
float64_t c 
)
virtual

update linear component

Parameters
docsdocs
labellabel
active2dnumactive 2D num
aa
a_oldold a
working2dnumworking 2D num
totdoctotdoc
linlin
aicacheai cache
cc

Reimplemented in CSVRLight.

Definition at line 1427 of file SVMLight.cpp.

void * update_linear_component_linadd_helper ( void *  p)
staticprotected

helper for update linear component linadd

Parameters
pp

Reimplemented in CSVRLight.

Definition at line 103 of file SVMLight.cpp.

void update_linear_component_mkl ( int32_t *  docs,
int32_t *  label,
int32_t *  active2dnum,
float64_t a,
float64_t a_old,
int32_t *  working2dnum,
int32_t  totdoc,
float64_t lin,
float64_t aicache 
)

update linear component MKL

Parameters
docsdocs
labellabel
active2dnumactive 2D num
aa
a_oldold a
working2dnumworking 2D num
totdoctotdoc
linlin
aicacheai cache

Definition at line 1524 of file SVMLight.cpp.

void update_linear_component_mkl_linadd ( int32_t *  docs,
int32_t *  label,
int32_t *  active2dnum,
float64_t a,
float64_t a_old,
int32_t *  working2dnum,
int32_t  totdoc,
float64_t lin,
float64_t aicache 
)

update linear component MKL

Parameters
docsdocs
labellabel
active2dnumactive 2D num
aa
a_oldold a
working2dnumworking 2D num
totdoctotdoc
linlin
aicacheai cache

Definition at line 1598 of file SVMLight.cpp.

void * update_linear_component_mkl_linadd_helper ( void *  p)
static

helper for update linear component MKL linadd

Parameters
pp

Definition at line 1672 of file SVMLight.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 250 of file SGObject.cpp.

Member Data Documentation

float64_t C1
protectedinherited

C1 regularization const

Definition at line 257 of file SVM.h.

float64_t C2
protectedinherited

C2

Definition at line 259 of file SVM.h.

bool(* callback)(CMKL *mkl, const float64_t *sumw, const float64_t suma)
protectedinherited

callback function svm optimizers may call when they have a new (small) set of alphas

Definition at line 269 of file SVM.h.

int32_t count
protected

number of iteration

Definition at line 681 of file SVMLight.h.

float64_t* dual
protected

dual

Definition at line 672 of file SVMLight.h.

float64_t epsilon
protectedinherited

epsilon

Definition at line 251 of file SVM.h.

int32_t init_iter
protected

init iter

Definition at line 662 of file SVMLight.h.

float64_t init_margin
protected

init margin

Definition at line 660 of file SVMLight.h.

SGIO* io
inherited

io

Definition at line 496 of file SGObject.h.

CKernel* kernel
protectedinherited

kernel

Definition at line 311 of file KernelMachine.h.

LEARN_PARM* learn_parm
protected

learn parameters

Definition at line 655 of file SVMLight.h.

SGVector<float64_t> m_alpha
protectedinherited

coefficients alpha

Definition at line 332 of file KernelMachine.h.

float64_t m_bias
protectedinherited

bias term b

Definition at line 329 of file KernelMachine.h.

CCustomKernel* m_custom_kernel
protectedinherited

is filled with pre-computed custom kernel on data lock

Definition at line 314 of file KernelMachine.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_backup
protectedinherited

old kernel is stored here on data lock

Definition at line 317 of file KernelMachine.h.

CLabels* m_labels
protectedinherited

labels

Definition at line 359 of file Machine.h.

SGVector<float64_t> m_linear_term
protectedinherited

linear term in qp

Definition at line 246 of file SVM.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.

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.

SGVector<int32_t> m_svs
protectedinherited

array of ``support vectors'' (indices of feature objects)

Definition at line 335 of file KernelMachine.h.

CMKL* mkl
protectedinherited

mkl object that svm optimizers need to pass when calling the callback function

Definition at line 272 of file SVM.h.

bool mkl_converged
protected

mkl converged

Definition at line 687 of file SVMLight.h.

MODEL* model
protected

model

Definition at line 653 of file SVMLight.h.

float64_t model_b
protected

model b

Definition at line 666 of file SVMLight.h.

float64_t mymaxdiff
protected

current alpha gap

Definition at line 683 of file SVMLight.h.

float64_t nu
protectedinherited

nu

Definition at line 255 of file SVM.h.

float64_t objective
protectedinherited

objective

Definition at line 261 of file SVM.h.

float64_t opt_precision
protected

opt precision

Definition at line 668 of file SVMLight.h.

Parallel* parallel
inherited

parallel

Definition at line 499 of file SGObject.h.

int32_t precision_violations
protected

precision violations

Definition at line 664 of file SVMLight.h.

float64_t* primal
protected

primal

Definition at line 670 of file SVMLight.h.

int32_t qpsize
protectedinherited

qpsize

Definition at line 263 of file SVM.h.

bool svm_loaded
protectedinherited

if SVM is loaded

Definition at line 249 of file SVM.h.

float64_t tube_epsilon
protectedinherited

tube epsilon for support vector regression

Definition at line 253 of file SVM.h.

bool use_batch_computation
protectedinherited

if batch computation is enabled

Definition at line 320 of file KernelMachine.h.

bool use_bias
protectedinherited

if bias shall be used

Definition at line 326 of file KernelMachine.h.

bool use_kernel_cache
protected

if kernel cache is used

Definition at line 685 of file SVMLight.h.

bool use_linadd
protectedinherited

if linadd is enabled

Definition at line 323 of file KernelMachine.h.

bool use_shrinking
protectedinherited

if shrinking shall be used

Definition at line 265 of file SVM.h.

int32_t verbosity
protected

verbosity level (0-4)

Definition at line 657 of file SVMLight.h.

Version* version
inherited

version

Definition at line 502 of file SGObject.h.

float64_t* W
protected

Matrix that stores the contribution by each kernel for each example (for current alphas)

Definition at line 679 of file SVMLight.h.


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

SHOGUN Machine Learning Toolbox - Documentation