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

CGUIClassifier Class Reference


Detailed Description

UI classifier.

Definition at line 24 of file GUIClassifier.h.

Inheritance diagram for CGUIClassifier:
Inheritance graph
[legend]

List of all members.

Public Member Functions

 CGUIClassifier ()
 CGUIClassifier (CSGInterface *interface)
 ~CGUIClassifier ()
bool new_classifier (char *name, int32_t d=6, int32_t from_d=40)
bool set_max_train_time (float64_t max)
bool load (char *filename, char *type)
bool save (char *param)
CLabelsclassify ()
CLabelsclassify_kernelmachine ()
CLabelsclassify_distancemachine ()
CLabelsclassify_linear ()
CLabelsclassify_byte_linear ()
bool classify_example (int32_t idx, float64_t &result)
CMachineget_classifier ()
bool get_trained_classifier (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols, int32_t idx=-1)
int32_t get_num_svms ()
bool get_svm (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols, int32_t idx=-1)
bool get_linear (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols)
bool get_clustering (float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols)
bool set_perceptron_parameters (float64_t lernrate, int32_t maxiter)
bool set_svm_C (float64_t C1, float64_t C2)
bool set_svm_bufsize (int32_t bufsize)
bool set_svm_qpsize (int32_t qpsize)
bool set_svm_max_qpsize (int32_t max_qpsize)
bool set_svm_shrinking_enabled (bool enabled)
bool set_svm_nu (float64_t nu)
bool set_svm_batch_computation_enabled (bool enabled)
bool set_do_auc_maximization (bool do_auc)
bool set_svm_linadd_enabled (bool enabled)
bool set_svm_bias_enabled (bool enabled)
bool set_mkl_interleaved_enabled (bool enabled)
bool set_svm_epsilon (float64_t epsilon)
bool set_svr_tube_epsilon (float64_t tube_epsilon)
bool set_svm_mkl_parameters (float64_t weight_epsilon, float64_t C_mkl, float64_t mkl_norm)
bool set_mkl_block_norm (float64_t mkl_bnorm)
bool set_elasticnet_lambda (float64_t lambda)
bool set_svm_precompute_enabled (int32_t precompute)
bool set_krr_tau (float64_t tau=1)
bool set_solver (char *solver)
bool set_constraint_generator (char *cg)
bool train_mkl_multiclass ()
bool train_mkl ()
bool train_svm ()
bool train_knn (int32_t k=3)
bool train_krr ()
bool train_clustering (int32_t k=3, int32_t max_iter=1000)
bool train_linear (float64_t gamma=0)
bool train_sparse_linear ()
bool train_wdocas ()
virtual const char * get_name () 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_PARAMETER)
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=VERSION_PARAMETER)
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_global_version ()
SGStringList< char > get_modelsel_names ()
void print_modsel_params ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)
void build_parameter_dictionary (CMap< TParameter *, CSGObject * > &dict)

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

virtual TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)
virtual void one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL)
virtual void load_serializable_pre () throw (ShogunException)
virtual void load_serializable_post () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)
virtual bool update_parameter_hash ()

Protected Attributes

CSGInterface * ui
CMachineclassifier
float64_t max_train_time
float64_t perceptron_learnrate
int32_t perceptron_maxiter
int32_t svm_qpsize
int32_t svm_bufsize
int32_t svm_max_qpsize
float64_t mkl_norm
float64_t mkl_block_norm
float64_t ent_lambda
float64_t svm_weight_epsilon
float64_t svm_epsilon
float64_t svm_tube_epsilon
float64_t svm_nu
float64_t svm_C1
float64_t svm_C2
float64_t C_mkl
float64_t krr_tau
bool mkl_use_interleaved
bool svm_use_bias
bool svm_use_batch_computation
bool svm_use_linadd
bool svm_use_precompute
bool svm_use_precompute_subkernel
bool svm_use_precompute_subkernel_light
bool svm_use_shrinking
bool svm_do_auc_maximization
CSVMconstraint_generator
ESolverType solver_type

Constructor & Destructor Documentation

CGUIClassifier (  ) 

constructor

Definition at line 28 of file GUIClassifier.h.

CGUIClassifier ( CSGInterface *  interface  ) 

constructor

Parameters:
interface 

Definition at line 71 of file GUIClassifier.cpp.

~CGUIClassifier (  ) 

destructor

Definition at line 110 of file GUIClassifier.cpp.


Member Function Documentation

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

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

Parameters:
dict dictionary of parameters to be built.

Definition at line 1201 of file SGObject.cpp.

CLabels * classify (  ) 

classify

Definition at line 1123 of file GUIClassifier.cpp.

CLabels * classify_byte_linear (  ) 

classify byte linear

Definition at line 1460 of file GUIClassifier.cpp.

CLabels * classify_distancemachine (  ) 

classify distance machine

Definition at line 1398 of file GUIClassifier.cpp.

bool classify_example ( int32_t  idx,
float64_t result 
)

classify example

Parameters:
idx 
result 

Definition at line 1486 of file GUIClassifier.cpp.

CLabels * classify_kernelmachine (  ) 

classify kernel machine

Definition at line 1173 of file GUIClassifier.cpp.

CLabels * classify_linear (  ) 

classify linear

Definition at line 1435 of file GUIClassifier.cpp.

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

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

Definition at line 131 of file SGObject.h.

CMachine* get_classifier (  ) 

get classifier

Definition at line 62 of file GUIClassifier.h.

bool get_clustering ( float64_t *&  weights,
int32_t &  rows,
int32_t &  cols,
float64_t *&  bias,
int32_t &  brows,
int32_t &  bcols 
)

get clustering

Parameters:
weights 
rows 
cols 
bias 
brows 
bcols 

Definition at line 1318 of file GUIClassifier.cpp.

SGIO * get_global_io (  )  [inherited]

get the io object

Returns:
io object

Definition at line 224 of file SGObject.cpp.

Parallel * get_global_parallel (  )  [inherited]

get the parallel object

Returns:
parallel object

Definition at line 259 of file SGObject.cpp.

Version * get_global_version (  )  [inherited]

get the version object

Returns:
version object

Definition at line 272 of file SGObject.cpp.

bool get_linear ( float64_t *&  weights,
int32_t &  rows,
int32_t &  cols,
float64_t *&  bias,
int32_t &  brows,
int32_t &  bcols 
)

get linear

Parameters:
weights 
rows 
cols 
bias 
brows 
bcols 

Definition at line 1374 of file GUIClassifier.cpp.

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

Definition at line 1108 of file SGObject.cpp.

char * get_modsel_param_descr ( const char *  param_name  )  [inherited]

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

Parameters:
param_name name of the parameter
Returns:
description of the parameter

Definition at line 1132 of file SGObject.cpp.

index_t get_modsel_param_index ( const char *  param_name  )  [inherited]

Returns index of model selection parameter with provided index

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

Definition at line 1145 of file SGObject.cpp.

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

Implements CSGObject.

Definition at line 226 of file GUIClassifier.h.

int32_t get_num_svms (  ) 

get number of SVMs in Multiclass

Definition at line 1280 of file GUIClassifier.cpp.

bool get_svm ( float64_t *&  weights,
int32_t &  rows,
int32_t &  cols,
float64_t *&  bias,
int32_t &  brows,
int32_t &  bcols,
int32_t  idx = -1 
)

get svm

Parameters:
weights 
rows 
cols 
bias 
brows 
bcols 
idx 

Definition at line 1286 of file GUIClassifier.cpp.

bool get_trained_classifier ( float64_t *&  weights,
int32_t &  rows,
int32_t &  cols,
float64_t *&  bias,
int32_t &  brows,
int32_t &  bcols,
int32_t  idx = -1 
)

get trained classifier

Parameters:
weights 
rows 
cols 
bias 
brows 
bcols 
idx 

Definition at line 1223 of file GUIClassifier.cpp.

bool is_generic ( EPrimitiveType *  generic  )  const [virtual, inherited]

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

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

Definition at line 278 of file SGObject.cpp.

bool load ( char *  filename,
char *  type 
)

load classifier from file

Definition at line 832 of file GUIClassifier.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_version parameter version of the file
current_version version from which mapping begins (you want to use VERSION_PARAMETER for this in most cases)
file file to load from
prefix prefix for members
Returns:
(sorted) array of created TParameter instances with file data

Definition at line 679 of file SGObject.cpp.

DynArray< TParameter * > * load_file_parameters ( const SGParamInfo param_info,
int32_t  file_version,
CSerializableFile file,
const char *  prefix = "" 
) [inherited]

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

Parameters:
param_info information of parameter
file_version parameter version of the file, must be <= provided parameter version
file file to load from
prefix prefix for members
Returns:
new array with TParameter instances with the attached data

Definition at line 523 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = VERSION_PARAMETER 
) [virtual, inherited]

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

Parameters:
file where to load from
prefix prefix for members
param_version (optional) a parameter version different to (this is mainly for testing, better do not use)
Returns:
TRUE if done, otherwise FALSE

Reimplemented in CModelSelectionParameters.

Definition at line 354 of file SGObject.cpp.

void load_serializable_post (  )  throw (ShogunException) [protected, virtual, inherited]

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

Exceptions:
ShogunException Will be thrown if an error occurres.

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

Definition at line 1033 of file SGObject.cpp.

void load_serializable_pre (  )  throw (ShogunException) [protected, virtual, inherited]

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

Exceptions:
ShogunException Will be thrown if an error occurres.

Definition at line 1028 of file SGObject.cpp.

void map_parameters ( DynArray< TParameter * > *  param_base,
int32_t &  base_version,
DynArray< const SGParamInfo * > *  target_param_infos 
) [inherited]

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

Parameters:
param_base set of TParameter instances that are mapped to the provided target parameter infos
base_version version of the parameter base
target_param_infos set of SGParamInfo instances that specify the target parameter base

Definition at line 717 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
) [protected, virtual, inherited]

creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.

If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass

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

Definition at line 923 of file SGObject.cpp.

bool new_classifier ( char *  name,
int32_t  d = 6,
int32_t  from_d = 40 
)

create new classifier

Definition at line 116 of file GUIClassifier.cpp.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
) [protected, virtual, inherited]

This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)

Parameters:
param_base set of TParameter instances to use for migration
target parameter info for the resulting TParameter
replacement (used as output) here the TParameter instance which is returned by migration is created into
to_migrate the only source that is used for migration
old_name with this parameter, a name change may be specified

Definition at line 864 of file SGObject.cpp.

void print_modsel_params (  )  [inherited]

prints all parameter registered for model selection and their type

Definition at line 1084 of file SGObject.cpp.

void print_serializable ( const char *  prefix = ""  )  [virtual, inherited]

prints registered parameters out

Parameters:
prefix prefix for members

Definition at line 290 of file SGObject.cpp.

bool save ( char *  param  ) 

save

Parameters:
param 

Definition at line 864 of file GUIClassifier.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = VERSION_PARAMETER 
) [virtual, inherited]

Save this object to file.

Parameters:
file where to save the object; will be closed during returning if PREFIX is an empty string.
prefix prefix for members
param_version (optional) a parameter version different to (this is mainly for testing, better do not use)
Returns:
TRUE if done, otherwise FALSE

Reimplemented in CModelSelectionParameters.

Definition at line 296 of file SGObject.cpp.

void save_serializable_post (  )  throw (ShogunException) [protected, virtual, inherited]

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

Exceptions:
ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1043 of file SGObject.cpp.

void save_serializable_pre (  )  throw (ShogunException) [protected, virtual, inherited]

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

Exceptions:
ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1038 of file SGObject.cpp.

bool set_constraint_generator ( char *  cg  ) 

set constraint generator

Definition at line 1591 of file GUIClassifier.cpp.

bool set_do_auc_maximization ( bool  do_auc  ) 

set do auc maximization

Parameters:
do_auc 

Definition at line 1110 of file GUIClassifier.cpp.

bool set_elasticnet_lambda ( float64_t  lambda  ) 

set elasticnet lambda

Parameters:
lambda 

Definition at line 986 of file GUIClassifier.cpp.

void set_generic< floatmax_t > (  )  [inherited]

set generic type to T

void set_global_io ( SGIO io  )  [inherited]

set the io object

Parameters:
io io object to use

Definition at line 217 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel  )  [inherited]

set the parallel object

Parameters:
parallel parallel object to use

Definition at line 230 of file SGObject.cpp.

void set_global_version ( Version version  )  [inherited]

set the version object

Parameters:
version version object to use

Definition at line 265 of file SGObject.cpp.

bool set_krr_tau ( float64_t  tau = 1  ) 

set KRR's tau

Definition at line 1527 of file GUIClassifier.cpp.

bool set_max_train_time ( float64_t  max  ) 

set maximum train time

Definition at line 919 of file GUIClassifier.cpp.

bool set_mkl_block_norm ( float64_t  mkl_bnorm  ) 

set mkl block norm

Parameters:
mkl_bnorm 

Definition at line 995 of file GUIClassifier.cpp.

bool set_mkl_interleaved_enabled ( bool  enabled  ) 

set mkl interleaved enabled

Parameters:
enabled 

Definition at line 1099 of file GUIClassifier.cpp.

bool set_perceptron_parameters ( float64_t  lernrate,
int32_t  maxiter 
)

set perceptron parameters

Parameters:
lernrate 
maxiter 

Definition at line 891 of file GUIClassifier.cpp.

bool set_solver ( char *  solver  ) 

set solver type

Definition at line 1540 of file GUIClassifier.cpp.

bool set_svm_batch_computation_enabled ( bool  enabled  ) 

set svm batch computation enabled

Parameters:
enabled 

Definition at line 1066 of file GUIClassifier.cpp.

bool set_svm_bias_enabled ( bool  enabled  ) 

set svm bias enabled

Parameters:
enabled 

Definition at line 1088 of file GUIClassifier.cpp.

bool set_svm_bufsize ( int32_t  bufsize  ) 

set svm bufsize

Parameters:
bufsize 

Definition at line 1044 of file GUIClassifier.cpp.

bool set_svm_C ( float64_t  C1,
float64_t  C2 
)

set svm C

Parameters:
C1 
C2 

Definition at line 1005 of file GUIClassifier.cpp.

bool set_svm_epsilon ( float64_t  epsilon  ) 

set svm epsilon

Parameters:
epsilon 

Definition at line 908 of file GUIClassifier.cpp.

bool set_svm_linadd_enabled ( bool  enabled  ) 

set svm linadd enabled

Parameters:
enabled 

Definition at line 1077 of file GUIClassifier.cpp.

bool set_svm_max_qpsize ( int32_t  max_qpsize  ) 

set svm max qpsize

Parameters:
max_qpsize 

Definition at line 1033 of file GUIClassifier.cpp.

bool set_svm_mkl_parameters ( float64_t  weight_epsilon,
float64_t  C_mkl,
float64_t  mkl_norm 
)

set svm mkl parameters

Parameters:
weight_epsilon 
C_mkl 
mkl_norm 

Definition at line 965 of file GUIClassifier.cpp.

bool set_svm_nu ( float64_t  nu  ) 

set svm nu

Parameters:
nu 

Definition at line 954 of file GUIClassifier.cpp.

bool set_svm_precompute_enabled ( int32_t  precompute  ) 

set svm precompute enabled

Parameters:
precompute 
bool set_svm_qpsize ( int32_t  qpsize  ) 

set svm qpsize

Parameters:
qpsize 

Definition at line 1022 of file GUIClassifier.cpp.

bool set_svm_shrinking_enabled ( bool  enabled  ) 

set svm shrinking enabled

Parameters:
enabled 

Definition at line 1055 of file GUIClassifier.cpp.

bool set_svr_tube_epsilon ( float64_t  tube_epsilon  ) 

set svr tube epsilon

Parameters:
tube_epsilon 

Definition at line 932 of file GUIClassifier.cpp.

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

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

Reimplemented in CGaussianKernel.

Definition at line 122 of file SGObject.h.

bool train_clustering ( int32_t  k = 3,
int32_t  max_iter = 1000 
)

train clustering

Definition at line 648 of file GUIClassifier.cpp.

bool train_knn ( int32_t  k = 3  ) 

train K-nearest-neighbour

Definition at line 684 of file GUIClassifier.cpp.

bool train_krr (  ) 

train kernel ridge regression

Definition at line 711 of file GUIClassifier.cpp.

bool train_linear ( float64_t  gamma = 0  ) 

train linear classifier

Parameters:
gamma gamma parameter of LDA

Definition at line 748 of file GUIClassifier.cpp.

bool train_mkl (  ) 

train MKL

Definition at line 483 of file GUIClassifier.cpp.

bool train_mkl_multiclass (  ) 

train MKL multiclass

Definition at line 437 of file GUIClassifier.cpp.

bool train_sparse_linear (  ) 

train sparse linear classifier

bool train_svm (  ) 

train SVM

Definition at line 552 of file GUIClassifier.cpp.

bool train_wdocas (  ) 

train WD OCAS

Definition at line 808 of file GUIClassifier.cpp.

void unset_generic (  )  [inherited]

unset generic type

this has to be called in classes specializing a template class

Definition at line 285 of file SGObject.cpp.

bool update_parameter_hash (  )  [protected, virtual, inherited]

Updates the hash of current parameter combination.

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

Definition at line 237 of file SGObject.cpp.


Member Data Documentation

float64_t C_mkl [protected]

C mkl

Definition at line 264 of file GUIClassifier.h.

CMachine* classifier [protected]

classifier

Definition at line 232 of file GUIClassifier.h.

CSVM* constraint_generator [protected]

constraint generator

Definition at line 287 of file GUIClassifier.h.

float64_t ent_lambda [protected]

ent lambda

Definition at line 250 of file GUIClassifier.h.

SGIO* io [inherited]

io

Definition at line 462 of file SGObject.h.

float64_t krr_tau [protected]

krr tau

Definition at line 266 of file GUIClassifier.h.

uint32_t m_hash [inherited]

Hash of parameter values

Definition at line 480 of file SGObject.h.

model selection parameters

Definition at line 474 of file SGObject.h.

map for different parameter versions

Definition at line 477 of file SGObject.h.

Parameter* m_parameters [inherited]

parameters

Definition at line 471 of file SGObject.h.

max train time

Definition at line 234 of file GUIClassifier.h.

mkl block norm

Definition at line 248 of file GUIClassifier.h.

float64_t mkl_norm [protected]

mkl norm

Definition at line 246 of file GUIClassifier.h.

bool mkl_use_interleaved [protected]

mkl use interleaved

Definition at line 268 of file GUIClassifier.h.

Parallel* parallel [inherited]

parallel

Definition at line 465 of file SGObject.h.

perceptron learnrate

Definition at line 236 of file GUIClassifier.h.

int32_t perceptron_maxiter [protected]

perceptron maxiter

Definition at line 238 of file GUIClassifier.h.

ESolverType solver_type [protected]

solver type

Definition at line 289 of file GUIClassifier.h.

int32_t svm_bufsize [protected]

svm bufsize

Definition at line 242 of file GUIClassifier.h.

float64_t svm_C1 [protected]

svm C1

Definition at line 260 of file GUIClassifier.h.

float64_t svm_C2 [protected]

svm C2

Definition at line 262 of file GUIClassifier.h.

bool svm_do_auc_maximization [protected]

svm do auc maximization

Definition at line 284 of file GUIClassifier.h.

float64_t svm_epsilon [protected]

svm epsilon

Definition at line 254 of file GUIClassifier.h.

int32_t svm_max_qpsize [protected]

svm max qpsize

Definition at line 244 of file GUIClassifier.h.

float64_t svm_nu [protected]

svm nu

Definition at line 258 of file GUIClassifier.h.

int32_t svm_qpsize [protected]

svm qpsize

Definition at line 240 of file GUIClassifier.h.

svm tube epsilon

Definition at line 256 of file GUIClassifier.h.

bool svm_use_batch_computation [protected]

svm use batch computation

Definition at line 272 of file GUIClassifier.h.

bool svm_use_bias [protected]

svm use bias

Definition at line 270 of file GUIClassifier.h.

bool svm_use_linadd [protected]

svm use linadd

Definition at line 274 of file GUIClassifier.h.

bool svm_use_precompute [protected]

svm use precompute

Definition at line 276 of file GUIClassifier.h.

bool svm_use_precompute_subkernel [protected]

svm use precompute subkernel

Definition at line 278 of file GUIClassifier.h.

svm use precompute subkernel light

Definition at line 280 of file GUIClassifier.h.

bool svm_use_shrinking [protected]

svm use shrinking

Definition at line 282 of file GUIClassifier.h.

svm weight epsilon

Definition at line 252 of file GUIClassifier.h.

CSGInterface* ui [protected]

ui

Definition at line 230 of file GUIClassifier.h.

Version* version [inherited]

version

Definition at line 468 of file SGObject.h.


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SHOGUN Machine Learning Toolbox - Documentation