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CWDSVMOcas Class Reference

Detailed Description

class WDSVMOcas

Definition at line 28 of file WDSVMOcas.h.

Inheritance diagram for CWDSVMOcas:
Inheritance graph
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Public Member Functions

 MACHINE_PROBLEM_TYPE (PT_BINARY)
 CWDSVMOcas ()
 CWDSVMOcas (E_SVM_TYPE type)
 CWDSVMOcas (float64_t C, int32_t d, int32_t from_d, CStringFeatures< uint8_t > *traindat, CLabels *trainlab)
virtual ~CWDSVMOcas ()
virtual EMachineType get_classifier_type ()
void set_C (float64_t c_neg, float64_t c_pos)
float64_t get_C1 ()
float64_t get_C2 ()
void set_epsilon (float64_t eps)
float64_t get_epsilon ()
void set_features (CStringFeatures< uint8_t > *feat)
CStringFeatures< uint8_t > * get_features ()
void set_bias_enabled (bool enable_bias)
bool get_bias_enabled ()
void set_bufsize (int32_t sz)
int32_t get_bufsize ()
void set_degree (int32_t d, int32_t from_d)
int32_t get_degree ()
virtual CBinaryLabelsapply_binary (CFeatures *data=NULL)
virtual CRegressionLabelsapply_regression (CFeatures *data=NULL)
virtual float64_t apply_one (int32_t num)
void set_normalization_const ()
float64_t get_normalization_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 bool train_locked (SGVector< index_t > indices)
virtual CLabelsapply_locked (SGVector< index_t > indices)
virtual CBinaryLabelsapply_locked_binary (SGVector< index_t > indices)
virtual CRegressionLabelsapply_locked_regression (SGVector< index_t > indices)
virtual CMulticlassLabelsapply_locked_multiclass (SGVector< index_t > indices)
virtual CStructuredLabelsapply_locked_structured (SGVector< index_t > indices)
virtual CLatentLabelsapply_locked_latent (SGVector< index_t > indices)
virtual void data_lock (CLabels *labs, CFeatures *features)
virtual void post_lock (CLabels *labs, CFeatures *features)
virtual void data_unlock ()
virtual bool supports_locking () const
bool is_data_locked () const
virtual 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 ()

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

SGVector< float64_tapply_get_outputs (CFeatures *data)
int32_t set_wd_weights ()
virtual const char * get_name () const
virtual bool train_machine (CFeatures *data=NULL)
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_W (float64_t *sq_norm_W, float64_t *dp_WoldW, float64_t *alpha, uint32_t nSel, void *ptr)
static float64_t update_W (float64_t t, void *ptr)
static void * add_new_cut_helper (void *ptr)
static int add_new_cut (float64_t *new_col_H, uint32_t *new_cut, uint32_t cut_length, uint32_t nSel, void *ptr)
static void * compute_output_helper (void *ptr)
static int compute_output (float64_t *output, void *ptr)
static int sort (float64_t *vals, float64_t *data, uint32_t size)
static void print (ocas_return_value_T value)

Protected Attributes

CStringFeatures< uint8_t > * features
bool use_bias
int32_t bufsize
float64_t C1
float64_t C2
float64_t epsilon
E_SVM_TYPE method
int32_t degree
int32_t from_degree
float32_twd_weights
int32_t num_vec
int32_t string_length
int32_t alphabet_size
float64_t normalization_const
float64_t bias
float64_t old_bias
int32_t * w_offsets
int32_t w_dim
int32_t w_dim_single_char
float32_tw
float32_told_w
float64_tlab
float32_t ** cuts
float64_tcp_bias
float64_t m_max_train_time
CLabelsm_labels
ESolverType m_solver_type
bool m_store_model_features
bool m_data_locked

Constructor & Destructor Documentation

default constructor

Definition at line 49 of file WDSVMOcas.cpp.

CWDSVMOcas ( E_SVM_TYPE  type)

constructor

Parameters
typetype of SVM

Definition at line 65 of file WDSVMOcas.cpp.

CWDSVMOcas ( float64_t  C,
int32_t  d,
int32_t  from_d,
CStringFeatures< uint8_t > *  traindat,
CLabels trainlab 
)

constructor

Parameters
Cconstant C
ddegree
from_dfrom degree
traindattraining features
trainlablabels for training features

Definition at line 79 of file WDSVMOcas.cpp.

~CWDSVMOcas ( )
virtual

Definition at line 96 of file WDSVMOcas.cpp.

Member Function Documentation

int add_new_cut ( float64_t new_col_H,
uint32_t *  new_cut,
uint32_t  cut_length,
uint32_t  nSel,
void *  ptr 
)
staticprotected

add new cut

Parameters
new_col_Hnew col H
new_cutnew cut
cut_lengthlength of cut
nSelnSel
ptrptr

Definition at line 352 of file WDSVMOcas.cpp.

void * add_new_cut_helper ( void *  ptr)
staticprotected

helper function for adding a new cut

Parameters
ptr
Returns
ptr

Definition at line 300 of file WDSVMOcas.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)
virtual

classify objects for binary classification problems

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

Reimplemented from CMachine.

Definition at line 100 of file WDSVMOcas.cpp.

SGVector< float64_t > apply_get_outputs ( CFeatures data)
protected

get real outputs

Parameters
datafeatures to apply for

Definition at line 112 of file WDSVMOcas.cpp.

CLatentLabels * apply_latent ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of latent problem

Reimplemented in CLinearLatentMachine.

Definition at line 240 of file Machine.cpp.

CLabels * apply_locked ( SGVector< index_t indices)
virtualinherited

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

Parameters
indicesindex vector (of locked features) that is predicted

Definition at line 195 of file Machine.cpp.

CBinaryLabels * apply_locked_binary ( SGVector< index_t indices)
virtualinherited

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

Reimplemented in CKernelMachine, and CMultitaskLinearMachine.

Definition at line 246 of file Machine.cpp.

CLatentLabels * apply_locked_latent ( SGVector< index_t indices)
virtualinherited

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

Definition at line 274 of file Machine.cpp.

CMulticlassLabels * apply_locked_multiclass ( SGVector< index_t indices)
virtualinherited

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

Definition at line 260 of file Machine.cpp.

CRegressionLabels * apply_locked_regression ( SGVector< index_t indices)
virtualinherited

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

Reimplemented in CKernelMachine.

Definition at line 253 of file Machine.cpp.

CStructuredLabels * apply_locked_structured ( SGVector< index_t indices)
virtualinherited

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

Definition at line 267 of file Machine.cpp.

CMulticlassLabels * apply_multiclass ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of multiclass classification problem

Reimplemented in CNeuralNetwork, CMulticlassMachine, CKNN, CID3ClassifierTree, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CQDA, CRelaxedTree, and CBaggingMachine.

Definition at line 228 of file Machine.cpp.

virtual float64_t apply_one ( int32_t  num)
virtual

classify one example

Parameters
numnumber of example to classify
Returns
classified result

Reimplemented from CMachine.

Definition at line 177 of file WDSVMOcas.h.

CRegressionLabels * apply_regression ( CFeatures data = NULL)
virtual

classify objects for regression problems

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

Reimplemented from CMachine.

Definition at line 106 of file WDSVMOcas.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 1185 of file SGObject.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 1302 of file SGObject.cpp.

int compute_output ( float64_t output,
void *  ptr 
)
staticprotected

compute output

Parameters
outputoutput
ptrptr

Definition at line 542 of file WDSVMOcas.cpp.

void * compute_output_helper ( void *  ptr)
staticprotected

helper function for computing the output

Parameters
ptr
Returns
ptr

Definition at line 450 of file WDSVMOcas.cpp.

void compute_W ( float64_t sq_norm_W,
float64_t dp_WoldW,
float64_t alpha,
uint32_t  nSel,
void *  ptr 
)
staticprotected

compute W

Parameters
sq_norm_Wsquare normed W
dp_WoldWdp W old W
alphaalpha
nSelnSel
ptrptr

Definition at line 612 of file WDSVMOcas.cpp.

void data_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

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

Only possible if supports_locking() returns true

Parameters
labslabels used for locking
featuresfeatures used for locking

Reimplemented in CKernelMachine.

Definition at line 120 of file Machine.cpp.

void data_unlock ( )
virtualinherited

Unlocks a locked machine and restores previous state

Reimplemented in CKernelMachine.

Definition at line 151 of file Machine.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 146 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 1206 of file SGObject.cpp.

bool get_bias_enabled ( )

check if bias is enabled

Returns
if bias is enabled

Definition at line 125 of file WDSVMOcas.h.

int32_t get_bufsize ( )

get buffer size

Returns
buffer size

Definition at line 137 of file WDSVMOcas.h.

float64_t get_C1 ( )

get C1

Returns
C1

Definition at line 74 of file WDSVMOcas.h.

float64_t get_C2 ( )

get C2

Returns
C2

Definition at line 80 of file WDSVMOcas.h.

virtual EMachineType get_classifier_type ( )
virtual

get classifier type

Returns
classifier type WDSVMOCAS

Reimplemented from CMachine.

Definition at line 60 of file WDSVMOcas.h.

int32_t get_degree ( )

get degree

Returns
degree

Definition at line 154 of file WDSVMOcas.h.

float64_t get_epsilon ( )

get epsilon

Returns
epsilon

Definition at line 92 of file WDSVMOcas.h.

CStringFeatures<uint8_t>* get_features ( )

get features

Returns
features

Definition at line 109 of file WDSVMOcas.h.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 183 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 224 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 237 of file SGObject.cpp.

CLabels * get_labels ( )
virtualinherited

get labels

Returns
labels

Definition at line 84 of file Machine.cpp.

virtual EProblemType get_machine_problem_type ( ) const
virtualinherited

returns type of problem machine solves

Reimplemented in CNeuralNetwork, and CBaseMulticlassMachine.

Definition at line 293 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 1077 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 1101 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 1114 of file SGObject.cpp.

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

Reimplemented from CMachine.

Definition at line 307 of file WDSVMOcas.h.

float64_t get_normalization_const ( )

get normalization const

Returns
normalization const

Definition at line 221 of file WDSVMOcas.h.

ESolverType get_solver_type ( )
inherited

get solver type

Returns
solver

Definition at line 110 of file Machine.cpp.

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

Definition at line 290 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 243 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, CGaussianProcessBinaryClassification, CGaussianProcessRegression, and CBaseMulticlassMachine.

Definition at line 342 of file Machine.h.

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

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

Parameters
file_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 648 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 489 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 320 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 occurres.

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

Definition at line 1004 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 occurres.

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

Definition at line 999 of file SGObject.cpp.

MACHINE_PROBLEM_TYPE ( PT_BINARY  )

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 686 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 893 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 833 of file SGObject.cpp.

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

Definition at line 209 of file SGObject.cpp.

virtual void post_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

post lock

Reimplemented in CMultitaskLinearMachine.

Definition at line 281 of file Machine.h.

static void print ( ocas_return_value_T  value)
staticprotected

print nothing

Definition at line 300 of file WDSVMOcas.h.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1053 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 255 of file SGObject.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 261 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 occurres.

Reimplemented in CKernel.

Definition at line 1014 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 occurres.

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

Definition at line 1009 of file SGObject.cpp.

void set_bias_enabled ( bool  enable_bias)

set if bias shall be enabled

Parameters
enable_biasif bias shall be enabled

Definition at line 119 of file WDSVMOcas.h.

void set_bufsize ( int32_t  sz)

set buffer size

Parameters
szbuffer size

Definition at line 131 of file WDSVMOcas.h.

void set_C ( float64_t  c_neg,
float64_t  c_pos 
)

set C

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

Definition at line 68 of file WDSVMOcas.h.

void set_degree ( int32_t  d,
int32_t  from_d 
)

set degree

Parameters
ddegree
from_dfrom degree

Definition at line 144 of file WDSVMOcas.h.

void set_epsilon ( float64_t  eps)

set epsilon

Parameters
epsnew epsilon

Definition at line 86 of file WDSVMOcas.h.

void set_features ( CStringFeatures< uint8_t > *  feat)

set features

Parameters
featfeatures to set

Definition at line 98 of file WDSVMOcas.h.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 38 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 176 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 189 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 230 of file SGObject.cpp.

void set_labels ( CLabels lab)
virtualinherited

set labels

Parameters
lablabels

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

Definition at line 73 of file Machine.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_normalization_const ( )

set normalization const

Definition at line 206 of file WDSVMOcas.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.

int32_t set_wd_weights ( )
protected

set wd weights

Returns
w_dim_single_c

Definition at line 144 of file WDSVMOcas.cpp.

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 140 of file SGObject.cpp.

int sort ( float64_t vals,
float64_t data,
uint32_t  size 
)
staticprotected

sort

Parameters
valsvals
datadata
sizesize

Definition at line 439 of file WDSVMOcas.cpp.

virtual void store_model_features ( )
protectedvirtualinherited

Stores feature data of underlying model. After this method has been called, it is possible to change the machine's feature data and call apply(), which is then performed on the training feature data that is part of the machine's model.

Base method, has to be implemented in order to allow cross-validation and model selection.

NOT IMPLEMENTED! Has to be done in subclasses

Reimplemented in CKernelMachine, CKNN, CLinearMulticlassMachine, CLinearMachine, CHierarchical, CDistanceMachine, CGaussianProcessMachine, CKernelMulticlassMachine, and CLinearStructuredOutputMachine.

Definition at line 329 of file Machine.h.

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

Reimplemented in CKernelMachine, and CMultitaskLinearMachine.

Definition at line 287 of file Machine.h.

bool train ( CFeatures data = NULL)
virtualinherited

train machine

Parameters
datatraining data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data). If flag is set, model features will be stored after training.
Returns
whether training was successful

Reimplemented in CRelaxedTree, CSGDQN, and COnlineSVMSGD.

Definition at line 47 of file Machine.cpp.

virtual bool train_locked ( SGVector< index_t indices)
virtualinherited

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

NOT IMPLEMENTED

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

Reimplemented in CKernelMachine, and CMultitaskLinearMachine.

Definition at line 233 of file Machine.h.

bool train_machine ( CFeatures data = NULL)
protectedvirtual

train 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.

Definition at line 162 of file WDSVMOcas.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 348 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 250 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 196 of file SGObject.cpp.

float64_t update_W ( float64_t  t,
void *  ptr 
)
staticprotected

update W

Parameters
tt
ptrptr
Returns
something floaty

Definition at line 267 of file WDSVMOcas.cpp.

Member Data Documentation

int32_t alphabet_size
protected

size of alphabet

Definition at line 347 of file WDSVMOcas.h.

float64_t bias
protected

bias

Definition at line 353 of file WDSVMOcas.h.

int32_t bufsize
protected

buffer size

Definition at line 326 of file WDSVMOcas.h.

float64_t C1
protected

C1

Definition at line 328 of file WDSVMOcas.h.

float64_t C2
protected

C2

Definition at line 330 of file WDSVMOcas.h.

float64_t* cp_bias
protected

bias dimensions

Definition at line 372 of file WDSVMOcas.h.

float32_t** cuts
protected

cuts

Definition at line 370 of file WDSVMOcas.h.

int32_t degree
protected

degree

Definition at line 337 of file WDSVMOcas.h.

float64_t epsilon
protected

epsilon

Definition at line 332 of file WDSVMOcas.h.

CStringFeatures<uint8_t>* features
protected

features

Definition at line 322 of file WDSVMOcas.h.

int32_t from_degree
protected

from degree

Definition at line 339 of file WDSVMOcas.h.

SGIO* io
inherited

io

Definition at line 461 of file SGObject.h.

float64_t* lab
protected

labels

Definition at line 367 of file WDSVMOcas.h.

bool m_data_locked
protectedinherited

whether data is locked

Definition at line 364 of file Machine.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 476 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 482 of file SGObject.h.

CLabels* m_labels
protectedinherited

labels

Definition at line 355 of file Machine.h.

float64_t m_max_train_time
protectedinherited

maximum training time

Definition at line 352 of file Machine.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 473 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 479 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 470 of file SGObject.h.

ESolverType m_solver_type
protectedinherited

solver type

Definition at line 358 of file Machine.h.

bool m_store_model_features
protectedinherited

whether model features should be stored after training

Definition at line 361 of file Machine.h.

E_SVM_TYPE method
protected

method

Definition at line 334 of file WDSVMOcas.h.

float64_t normalization_const
protected

normalization const

Definition at line 350 of file WDSVMOcas.h.

int32_t num_vec
protected

num vectors

Definition at line 343 of file WDSVMOcas.h.

float64_t old_bias
protected

old_bias

Definition at line 355 of file WDSVMOcas.h.

float32_t* old_w
protected

old w

Definition at line 365 of file WDSVMOcas.h.

Parallel* parallel
inherited

parallel

Definition at line 464 of file SGObject.h.

int32_t string_length
protected

length of string in vector

Definition at line 345 of file WDSVMOcas.h.

bool use_bias
protected

if bias shall be used

Definition at line 324 of file WDSVMOcas.h.

Version* version
inherited

version

Definition at line 467 of file SGObject.h.

float32_t* w
protected

w

Definition at line 363 of file WDSVMOcas.h.

int32_t w_dim
protected

w dim

Definition at line 359 of file WDSVMOcas.h.

int32_t w_dim_single_char
protected

w dim of a single char

Definition at line 361 of file WDSVMOcas.h.

int32_t* w_offsets
protected

w offsets

Definition at line 357 of file WDSVMOcas.h.

float32_t* wd_weights
protected

wd weights

Definition at line 341 of file WDSVMOcas.h.


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

SHOGUN Machine Learning Toolbox - Documentation