Detailed Description

UI classifier.

Definition at line 24 of file GUIClassifier.h.

Inheritance diagram for CGUIClassifier:

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)
CLabels *	classify ()
CLabels *	classify_kernelmachine ()
CLabels *	classify_distancemachine ()
CLabels *	classify_linear ()
CLabels *	classify_byte_linear ()
bool	classify_example (int32_t idx, float64_t &result)
CMachine *	get_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 CSGObject *	shallow_copy () const
virtual CSGObject *	deep_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)
SGIO *	get_global_io ()
void	set_global_parallel (Parallel *parallel)
Parallel *	get_global_parallel ()
void	set_global_version (Version *version)
Version *	get_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 bool	update_parameter_hash ()
virtual bool	equals (CSGObject *other, float64_t accuracy=0.0)
virtual CSGObject *	clone ()

Public Attributes
SGIO *	io
Parallel *	parallel
Version *	version
Parameter *	m_parameters
Parameter *	m_model_selection_parameters
Parameter *	m_gradient_parameters
ParameterMap *	m_parameter_map
uint32_t	m_hash

Protected Member Functions
virtual TParameter *	migrate (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
CSGInterface *	ui
CMachine *	classifier
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
CSVM *	constraint_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 69 of file GUIClassifier.cpp.

~CGUIClassifier ( )

destructor

Definition at line 108 of file GUIClassifier.cpp.

Member Function Documentation

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

dict	dictionary of parameters to be built.

Definition at line 1196 of file SGObject.cpp.

CLabels * classify ( )

classify

Definition at line 1092 of file GUIClassifier.cpp.

CLabels * classify_byte_linear ( )

classify byte linear

Definition at line 1426 of file GUIClassifier.cpp.

CLabels * classify_distancemachine ( )

classify distance machine

Definition at line 1364 of file GUIClassifier.cpp.

bool classify_example	(	int32_t	idx,
		float64_t &	result
	)

classify example

Parameters

idx
result

Definition at line 1452 of file GUIClassifier.cpp.

CLabels * classify_kernelmachine ( )

classify kernel machine

Definition at line 1140 of file GUIClassifier.cpp.

CLabels * classify_linear ( )

classify linear

Definition at line 1401 of file GUIClassifier.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 1313 of file SGObject.cpp.

virtual CSGObject* deep_copy ( ) const

virtualinherited

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

Definition at line 160 of file SGObject.h.

bool equals	(	CSGObject *	other,
		float64_t	accuracy = `0.0`
	)

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

other	object to compare with
accuracy	accuracy to use for comparison (optional)

Returns: true if all parameters were equal, false if not

Definition at line 1217 of file SGObject.cpp.

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 1284 of file GUIClassifier.cpp.

SGIO * get_global_io ( )

inherited

get the io object

Returns: io object

Definition at line 214 of file SGObject.cpp.

Parallel * get_global_parallel ( )

inherited

get the parallel object

Returns: parallel object

Definition at line 249 of file SGObject.cpp.

Version * get_global_version ( )

inherited

get the version object

Returns: version object

Definition at line 262 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 1340 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 1100 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 1124 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 1137 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 1246 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 1252 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 1191 of file GUIClassifier.cpp.

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

generic set to the type of the generic if returning TRUE

Returns: TRUE if a class template.

Definition at line 268 of file SGObject.cpp.

bool load	(	char *	filename,
		char *	type
	)

load classifier from file

Definition at line 801 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::get_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 673 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 514 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

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

Definition at line 345 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

ShogunException Will be thrown if an error occurres.

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

Definition at line 1029 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

ShogunException Will be thrown if an error occurres.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicArray< uint64_t >, and CDynamicObjectArray.

Definition at line 1024 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 711 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_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 918 of file SGObject.cpp.

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

create new classifier

Definition at line 114 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`
	)

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_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 858 of file SGObject.cpp.

void print_modsel_params ( )

inherited

prints all parameter registered for model selection and their type

Definition at line 1076 of file SGObject.cpp.

void print_serializable ( const char * prefix = "" )

virtualinherited

prints registered parameters out

Parameters

prefix prefix for members

Definition at line 280 of file SGObject.cpp.

bool save ( char * param )

save

Parameters

param

Definition at line 833 of file GUIClassifier.cpp.

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

virtualinherited

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

Definition at line 286 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

ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1039 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

ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicArray< uint64_t >, and CDynamicObjectArray.

Definition at line 1034 of file SGObject.cpp.

bool set_constraint_generator ( char * cg )

set constraint generator

Definition at line 1557 of file GUIClassifier.cpp.

bool set_do_auc_maximization ( bool do_auc )

set do auc maximization

Parameters

do_auc

Definition at line 1079 of file GUIClassifier.cpp.

bool set_elasticnet_lambda ( float64_t lambda )

set elasticnet lambda

Parameters

lambda

Definition at line 955 of file GUIClassifier.cpp.

void set_generic< complex128_t > ( )

inherited

set generic type to T

Definition at line 41 of file SGObject.cpp.

void set_global_io ( SGIO * io )

inherited

set the io object

Parameters

io	io object to use

Definition at line 207 of file SGObject.cpp.

void set_global_parallel ( Parallel * parallel )

inherited

set the parallel object

Parameters

parallel parallel object to use

Definition at line 220 of file SGObject.cpp.

void set_global_version ( Version * version )

inherited

set the version object

Parameters

version version object to use

Definition at line 255 of file SGObject.cpp.

bool set_krr_tau ( float64_t tau = 1 )

set KRR's tau

Definition at line 1493 of file GUIClassifier.cpp.

bool set_max_train_time ( float64_t max )

set maximum train time

Definition at line 888 of file GUIClassifier.cpp.

bool set_mkl_block_norm ( float64_t mkl_bnorm )

set mkl block norm

Parameters

mkl_bnorm

Definition at line 964 of file GUIClassifier.cpp.

bool set_mkl_interleaved_enabled ( bool enabled )

set mkl interleaved enabled

Parameters

enabled

Definition at line 1068 of file GUIClassifier.cpp.

bool set_perceptron_parameters	(	float64_t	lernrate,
		int32_t	maxiter
	)

set perceptron parameters

Parameters

lernrate
maxiter

Definition at line 860 of file GUIClassifier.cpp.

bool set_solver ( char * solver )

set solver type

Definition at line 1506 of file GUIClassifier.cpp.

bool set_svm_batch_computation_enabled ( bool enabled )

set svm batch computation enabled

Parameters

enabled

Definition at line 1035 of file GUIClassifier.cpp.

bool set_svm_bias_enabled ( bool enabled )

set svm bias enabled

Parameters

enabled

Definition at line 1057 of file GUIClassifier.cpp.

bool set_svm_bufsize ( int32_t bufsize )

set svm bufsize

Parameters

bufsize

Definition at line 1013 of file GUIClassifier.cpp.

bool set_svm_C	(	float64_t	C1,
		float64_t	C2
	)

set svm C

Parameters

C1
C2

Definition at line 974 of file GUIClassifier.cpp.

bool set_svm_epsilon ( float64_t epsilon )

set svm epsilon

Parameters

epsilon

Definition at line 877 of file GUIClassifier.cpp.

bool set_svm_linadd_enabled ( bool enabled )

set svm linadd enabled

Parameters

enabled

Definition at line 1046 of file GUIClassifier.cpp.

bool set_svm_max_qpsize ( int32_t max_qpsize )

set svm max qpsize

Parameters

max_qpsize

Definition at line 1002 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 934 of file GUIClassifier.cpp.

bool set_svm_nu ( float64_t nu )

set svm nu

Parameters

nu

Definition at line 923 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 991 of file GUIClassifier.cpp.

bool set_svm_shrinking_enabled ( bool enabled )

set svm shrinking enabled

Parameters

enabled

Definition at line 1024 of file GUIClassifier.cpp.

bool set_svr_tube_epsilon ( float64_t tube_epsilon )

set svr tube epsilon

Parameters

tube_epsilon

Definition at line 901 of file GUIClassifier.cpp.

virtual 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 151 of file SGObject.h.

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

train clustering

Definition at line 620 of file GUIClassifier.cpp.

bool train_knn ( int32_t k = 3 )

train K-nearest-neighbour

Definition at line 656 of file GUIClassifier.cpp.

bool train_krr ( )

train kernel ridge regression

Definition at line 683 of file GUIClassifier.cpp.

bool train_linear ( float64_t gamma = 0 )

train linear classifier

Parameters

gamma gamma parameter of LDA

Definition at line 720 of file GUIClassifier.cpp.

bool train_mkl ( )

train MKL

Definition at line 455 of file GUIClassifier.cpp.

bool train_mkl_multiclass ( )

train MKL multiclass

Definition at line 409 of file GUIClassifier.cpp.

bool train_sparse_linear ( )

train sparse linear classifier

bool train_svm ( )

train SVM

Definition at line 524 of file GUIClassifier.cpp.

bool train_wdocas ( )

train WD OCAS

Definition at line 777 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 275 of file SGObject.cpp.

bool update_parameter_hash ( )

virtualinherited

Updates the hash of current parameter combination.

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

Definition at line 227 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 514 of file SGObject.h.

float64_t krr_tau

protected

krr tau

Definition at line 266 of file GUIClassifier.h.

Parameter* m_gradient_parameters

inherited

parameters wrt which we can compute gradients

Definition at line 529 of file SGObject.h.

uint32_t m_hash

inherited

Hash of parameter values

Definition at line 535 of file SGObject.h.

Parameter* m_model_selection_parameters

inherited

model selection parameters

Definition at line 526 of file SGObject.h.

ParameterMap* m_parameter_map

inherited

map for different parameter versions

Definition at line 532 of file SGObject.h.

Parameter* m_parameters

inherited

parameters

Definition at line 523 of file SGObject.h.

float64_t max_train_time

protected

max train time

Definition at line 234 of file GUIClassifier.h.

float64_t mkl_block_norm

protected

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 517 of file SGObject.h.

float64_t perceptron_learnrate

protected

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.

float64_t svm_tube_epsilon

protected

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.

bool svm_use_precompute_subkernel_light

protected

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.

float64_t svm_weight_epsilon

protected

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 520 of file SGObject.h.

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

Detailed Description

Public Member Functions

Public Attributes

Protected Member Functions

Protected Attributes

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation