SHOGUN  6.0.0
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros Modules
List of all members | Public Member Functions | Static Public Member Functions | Public Attributes | Protected Member Functions | Protected Attributes
CLibSVMOneClass Class Reference

Detailed Description

class LibSVMOneClass

Definition at line 25 of file LibSVMOneClass.h.

Inheritance diagram for CLibSVMOneClass:
[legend]

Public Member Functions

 CLibSVMOneClass ()
 
 CLibSVMOneClass (float64_t C, CKernel *k)
 
virtual ~CLibSVMOneClass ()
 
virtual EMachineType get_classifier_type ()
 
virtual const char * get_name () const
 
 MACHINE_PROBLEM_TYPE (PT_BINARY)
 
void set_defaults (int32_t num_sv=0)
 
virtual SGVector< float64_t > get_linear_term ()
 
virtual void set_linear_term (const SGVector< float64_t > linear_term)
 
bool load (FILE *svm_file)
 
bool save (FILE *svm_file)
 
void set_nu (float64_t nue)
 
void set_C (float64_t c_neg, float64_t c_pos)
 
void set_epsilon (float64_t eps)
 
void set_tube_epsilon (float64_t eps)
 
float64_t get_tube_epsilon ()
 
void set_qpsize (int32_t qps)
 
float64_t get_epsilon ()
 
float64_t get_nu ()
 
float64_t get_C1 ()
 
float64_t get_C2 ()
 
int32_t get_qpsize ()
 
void set_shrinking_enabled (bool enable)
 
bool get_shrinking_enabled ()
 
float64_t compute_svm_dual_objective ()
 
float64_t compute_svm_primal_objective ()
 
void set_objective (float64_t v)
 
float64_t get_objective ()
 
bool get_loaded_status ()
 
void set_loaded_status (bool loaded)
 
void set_callback_function (CMKL *m, bool(*cb)(CMKL *mkl, const float64_t *sumw, const float64_t suma))
 
void set_kernel (CKernel *k)
 
CKernel * get_kernel ()
 
void set_batch_computation_enabled (bool enable)
 
bool get_batch_computation_enabled ()
 
void set_linadd_enabled (bool enable)
 
bool get_linadd_enabled ()
 
void set_bias_enabled (bool enable_bias)
 
bool get_bias_enabled ()
 
float64_t get_bias ()
 
void set_bias (float64_t bias)
 
int32_t get_support_vector (int32_t idx)
 
float64_t get_alpha (int32_t idx)
 
bool set_support_vector (int32_t idx, int32_t val)
 
bool set_alpha (int32_t idx, float64_t val)
 
int32_t get_num_support_vectors ()
 
void set_alphas (SGVector< float64_t > alphas)
 
void set_support_vectors (SGVector< int32_t > svs)
 
SGVector< int32_t > get_support_vectors ()
 
SGVector< float64_t > get_alphas ()
 
bool create_new_model (int32_t num)
 
bool init_kernel_optimization ()
 
virtual CRegressionLabels * apply_regression (CFeatures *data=NULL)
 
virtual CBinaryLabels * apply_binary (CFeatures *data=NULL)
 
virtual float64_t apply_one (int32_t num)
 
virtual bool train_locked (SGVector< index_t > indices)
 
virtual CBinaryLabels * apply_locked_binary (SGVector< index_t > indices)
 
virtual CRegressionLabels * apply_locked_regression (SGVector< index_t > indices)
 
virtual SGVector< float64_t > apply_locked_get_output (SGVector< index_t > indices)
 
virtual void data_lock (CLabels *labs, CFeatures *features=NULL)
 
virtual void data_unlock ()
 
virtual bool supports_locking () const
 
virtual bool train (CFeatures *data=NULL)
 
virtual CLabels * apply (CFeatures *data=NULL)
 
virtual CMulticlassLabels * apply_multiclass (CFeatures *data=NULL)
 
virtual CStructuredLabels * apply_structured (CFeatures *data=NULL)
 
virtual CLatentLabels * apply_latent (CFeatures *data=NULL)
 
virtual void set_labels (CLabels *lab)
 
virtual CLabels * get_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 CLabels * apply_locked (SGVector< index_t > indices)
 
virtual CMulticlassLabels * apply_locked_multiclass (SGVector< index_t > indices)
 
virtual CStructuredLabels * apply_locked_structured (SGVector< index_t > indices)
 
virtual CLatentLabels * apply_locked_latent (SGVector< index_t > indices)
 
virtual void post_lock (CLabels *labs, CFeatures *features)
 
bool is_data_locked () const
 
virtual EProblemType get_machine_problem_type () const
 
virtual CSGObject * shallow_copy () const
 
virtual CSGObject * deep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
 
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)
 
bool has (const std::string &name) const
 
template<typename T >
bool has (const Tag< T > &tag) const
 
template<typename T , typename U = void>
bool has (const std::string &name) const
 
template<typename T >
void set (const Tag< T > &_tag, const T &value)
 
template<typename T , typename U = void>
void set (const std::string &name, const T &value)
 
template<typename T >
T get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
T get (const std::string &name) const
 
virtual void update_parameter_hash ()
 
virtual bool parameter_hash_changed ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
 
virtual CSGObject * clone ()
 

Static Public Member Functions

static void * apply_helper (void *p)
 

Public Attributes

SGIO * io
 
Parallel * parallel
 
Version * version
 
Parameter * m_parameters
 
Parameter * m_model_selection_parameters
 
Parameter * m_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

virtual bool train_require_labels () const
 
virtual bool train_machine (CFeatures *data=NULL)
 
virtual float64_t * get_linear_term_array ()
 
SGVector< float64_t > apply_get_outputs (CFeatures *data)
 
virtual void store_model_features ()
 
virtual bool is_label_valid (CLabels *lab) const
 
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)
 
template<typename T >
void register_param (Tag< T > &_tag, const T &value)
 
template<typename T >
void register_param (const std::string &name, const T &value)
 
bool clone_parameters (CSGObject *other)
 

Protected Attributes

SGVector< float64_t > m_linear_term
 
bool svm_loaded
 
float64_t epsilon
 
float64_t tube_epsilon
 
float64_t nu
 
float64_t C1
 
float64_t C2
 
float64_t objective
 
int32_t qpsize
 
bool use_shrinking
 
bool(* callback )(CMKL *mkl, const float64_t *sumw, const float64_t suma)
 
CMKL * mkl
 
CKernel * kernel
 
CCustomKernel * m_custom_kernel
 
CKernel * m_kernel_backup
 
bool use_batch_computation
 
bool use_linadd
 
bool use_bias
 
float64_t m_bias
 
SGVector< float64_t > m_alpha
 
SGVector< int32_t > m_svs
 
float64_t m_max_train_time
 
CLabels * m_labels
 
ESolverType m_solver_type
 
bool m_store_model_features
 
bool m_data_locked
 

Constructor & Destructor Documentation

CLibSVMOneClass ( )

default constructor

Definition at line 17 of file LibSVMOneClass.cpp.

CLibSVMOneClass ( float64_t  C,
CKernel *  k 
)

constructor

Parameters
Cconstant C
kkernel

Definition at line 22 of file LibSVMOneClass.cpp.

~CLibSVMOneClass ( )
virtual

Definition at line 27 of file LibSVMOneClass.cpp.

Member Function Documentation

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 152 of file Machine.cpp.

CBinaryLabels * apply_binary ( CFeatures *  data = NULL)
virtualinherited

apply kernel machine to data for binary classification task

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

Reimplemented from CMachine.

Reimplemented in CDomainAdaptationSVM.

Definition at line 248 of file KernelMachine.cpp.

SGVector< float64_t > apply_get_outputs ( CFeatures *  data)
protectedinherited

apply get outputs

Parameters
datafeatures to compute outputs
Returns
outputs

Definition at line 254 of file KernelMachine.cpp.

void * apply_helper ( void *  p)
staticinherited

apply example helper, used in threads

Parameters
pparams of the thread
Returns
nothing really

Definition at line 429 of file KernelMachine.cpp.

CLatentLabels * apply_latent ( CFeatures *  data = NULL)
virtualinherited

apply machine to data in means of latent problem

Reimplemented in CLinearLatentMachine.

Definition at line 232 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 187 of file Machine.cpp.

CBinaryLabels * apply_locked_binary ( SGVector< index_t >  indices)
virtualinherited

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

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

Reimplemented from CMachine.

Definition at line 523 of file KernelMachine.cpp.

SGVector< float64_t > apply_locked_get_output ( SGVector< index_t >  indices)
virtualinherited

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

Parameters
indicesindex vector (of locked features) that is predicted
Returns
raw output of machine

Definition at line 536 of file KernelMachine.cpp.

CLatentLabels * apply_locked_latent ( SGVector< index_t >  indices)
virtualinherited

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

Definition at line 266 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 252 of file Machine.cpp.

CRegressionLabels * apply_locked_regression ( SGVector< index_t >  indices)
virtualinherited

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

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

Reimplemented from CMachine.

Definition at line 529 of file KernelMachine.cpp.

CStructuredLabels * apply_locked_structured ( SGVector< index_t >  indices)
virtualinherited

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

Definition at line 259 of file Machine.cpp.

CMulticlassLabels * apply_multiclass ( CFeatures *  data = NULL)
virtualinherited

apply machine to data in means of multiclass classification problem

Reimplemented in CNeuralNetwork, CCHAIDTree, CCARTree, CGaussianProcessClassification, CKNN, CMulticlassMachine, CC45ClassifierTree, CID3ClassifierTree, CQDA, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CRelaxedTree, and CBaggingMachine.

Definition at line 220 of file Machine.cpp.

float64_t apply_one ( int32_t  num)
virtualinherited

apply kernel machine to one example

Parameters
numwhich example to apply to
Returns
classified value

Reimplemented from CMachine.

Definition at line 410 of file KernelMachine.cpp.

CRegressionLabels * apply_regression ( CFeatures *  data = NULL)
virtualinherited

apply kernel machine to data for regression task

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

Reimplemented from CMachine.

Definition at line 242 of file KernelMachine.cpp.

CStructuredLabels * apply_structured ( CFeatures *  data = NULL)
virtualinherited

apply machine to data in means of SO classification problem

Reimplemented in CLinearStructuredOutputMachine.

Definition at line 226 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 630 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

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

Definition at line 729 of file SGObject.cpp.

bool clone_parameters ( CSGObject *  other)
protectedinherited

Definition at line 754 of file SGObject.cpp.

float64_t compute_svm_dual_objective ( )
inherited

compute svm dual objective

Returns
computed dual objective

Definition at line 237 of file SVM.cpp.

float64_t compute_svm_primal_objective ( )
inherited

compute svm primal objective

Returns
computed svm primal objective

Definition at line 262 of file SVM.cpp.

bool create_new_model ( int32_t  num)
inherited

create new model

Parameters
numnumber of alphas and support vectors in new model

Definition at line 194 of file KernelMachine.cpp.

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

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

Computes kernel matrix to speed up train/apply calls

Parameters
labslabels used for locking
featuresfeatures used for locking

Reimplemented from CMachine.

Definition at line 633 of file KernelMachine.cpp.

void data_unlock ( )
virtualinherited

Unlocks a locked machine and restores previous state

Reimplemented from CMachine.

Definition at line 664 of file KernelMachine.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 231 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 651 of file SGObject.cpp.

T get ( const Tag< T > &  _tag) const
inherited

Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
Returns
value of the parameter identified by the input tag

Definition at line 376 of file SGObject.h.

T get ( const std::string &  name) const
inherited

Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
Returns
value of the parameter corresponding to the input name and type

Definition at line 399 of file SGObject.h.

float64_t get_alpha ( int32_t  idx)
inherited

get alpha at given index

Parameters
idxindex of alpha
Returns
alpha

Definition at line 140 of file KernelMachine.cpp.

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

Definition at line 189 of file KernelMachine.cpp.

bool get_batch_computation_enabled ( )
inherited

check if batch computation is enabled

Returns
if batch computation is enabled

Definition at line 99 of file KernelMachine.cpp.

float64_t get_bias ( )
inherited

get bias

Returns
bias

Definition at line 124 of file KernelMachine.cpp.

bool get_bias_enabled ( )
inherited

get state of bias

Returns
state of bias

Definition at line 119 of file KernelMachine.cpp.

float64_t get_C1 ( )
inherited

get C1

Returns
C1

Definition at line 161 of file SVM.h.

float64_t get_C2 ( )
inherited

get C2

Returns
C2

Definition at line 167 of file SVM.h.

virtual EMachineType get_classifier_type ( )
virtual

get classifier type

Returns
classifier type LIBSVMONECLASS

Reimplemented from CMachine.

Definition at line 43 of file LibSVMOneClass.h.

float64_t get_epsilon ( )
inherited

get epsilon

Returns
epsilon

Definition at line 149 of file SVM.h.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 268 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 310 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 323 of file SGObject.cpp.

CKernel * get_kernel ( )
inherited

get kernel

Returns
kernel

Definition at line 88 of file KernelMachine.cpp.

CLabels * get_labels ( )
virtualinherited

get labels

Returns
labels

Definition at line 76 of file Machine.cpp.

bool get_linadd_enabled ( )
inherited

check if linadd is enabled

Returns
if linadd is enabled

Definition at line 109 of file KernelMachine.cpp.

SGVector< float64_t > get_linear_term ( )
virtualinherited

get linear term

Returns
the linear term

Definition at line 327 of file SVM.cpp.

float64_t * get_linear_term_array ( )
protectedvirtualinherited

get linear term copy as dynamic array

Returns
linear term copied to a dynamic array

Definition at line 297 of file SVM.cpp.

bool get_loaded_status ( )
inherited

check if svm been loaded

Returns
if svm_loaded is true

Definition at line 227 of file SVM.h.

virtual EProblemType get_machine_problem_type ( ) const
virtualinherited

returns type of problem machine solves

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

Definition at line 303 of file Machine.h.

float64_t get_max_train_time ( )
inherited

get maximum training time

Returns
maximum training time

Definition at line 87 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 531 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 555 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 568 of file SGObject.cpp.

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

Reimplemented from CSVM.

Definition at line 46 of file LibSVMOneClass.h.

float64_t get_nu ( )
inherited

get nu

Returns
nu

Definition at line 155 of file SVM.h.

int32_t get_num_support_vectors ( )
inherited

get number of support vectors

Returns
number of support vectors

Definition at line 169 of file KernelMachine.cpp.

float64_t get_objective ( )
inherited

get objective

Returns
objective

Definition at line 218 of file SVM.h.

int32_t get_qpsize ( )
inherited

get qpsize

Returns
qpsize

Definition at line 173 of file SVM.h.

bool get_shrinking_enabled ( )
inherited

get state of shrinking

Returns
if shrinking is enabled

Definition at line 188 of file SVM.h.

ESolverType get_solver_type ( )
inherited

get solver type

Returns
solver

Definition at line 102 of file Machine.cpp.

int32_t get_support_vector ( int32_t  idx)
inherited

get support vector at given index

Parameters
idxindex of support vector
Returns
support vector

Definition at line 134 of file KernelMachine.cpp.

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

Definition at line 184 of file KernelMachine.cpp.

float64_t get_tube_epsilon ( )
inherited

get tube epsilon

Returns
tube epsilon

Definition at line 137 of file SVM.h.

bool has ( const std::string &  name) const
inherited

Checks if object has a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name

Definition at line 299 of file SGObject.h.

bool has ( const Tag< T > &  tag) const
inherited

Checks if object has a class parameter identified by a Tag.

Parameters
tagtag of the parameter containing name and type information
Returns
true if the parameter exists with the input tag

Definition at line 310 of file SGObject.h.

bool has ( const std::string &  name) const
inherited

Checks if a type exists for a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name and type

Definition at line 321 of file SGObject.h.

bool init_kernel_optimization ( )
inherited

initialise kernel optimisation

Returns
if operation was successful

Definition at line 211 of file KernelMachine.cpp.

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

Definition at line 300 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 329 of file SGObject.cpp.

virtual bool is_label_valid ( CLabels *  lab) const
protectedvirtualinherited

check whether the labels is valid.

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

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

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

Definition at line 352 of file Machine.h.

bool load ( FILE *  svm_file)
inherited

load a SVM from file

Parameters
svm_filethe file handle

Definition at line 85 of file SVM.cpp.

bool load_serializable ( CSerializableFile *  file,
const char *  prefix = "" 
)
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
Returns
TRUE if done, otherwise FALSE

Definition at line 402 of file SGObject.cpp.

void load_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

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

Exceptions
ShogunExceptionwill be thrown if an error occurs.

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

Definition at line 459 of file SGObject.cpp.

void load_serializable_pre ( )
throw (ShogunException
)
protectedvirtualinherited

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

Exceptions
ShogunExceptionwill be thrown if an error occurs.

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

Definition at line 454 of file SGObject.cpp.

MACHINE_PROBLEM_TYPE ( PT_BINARY  )
inherited

problem type

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

Definition at line 295 of file SGObject.cpp.

virtual void post_lock ( CLabels *  labs,
CFeatures *  features 
)
virtualinherited

post lock

Definition at line 291 of file Machine.h.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 507 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 341 of file SGObject.cpp.

void register_param ( Tag< T > &  _tag,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 450 of file SGObject.h.

void register_param ( const std::string &  name,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 463 of file SGObject.h.

bool save ( FILE *  svm_file)
inherited

write a SVM to a file

Parameters
svm_filethe file handle

Definition at line 201 of file SVM.cpp.

bool save_serializable ( CSerializableFile *  file,
const char *  prefix = "" 
)
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
Returns
TRUE if done, otherwise FALSE

Definition at line 347 of file SGObject.cpp.

void save_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

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

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 469 of file SGObject.cpp.

void save_serializable_pre ( )
throw (ShogunException
)
protectedvirtualinherited

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

Exceptions
ShogunExceptionwill be thrown if an error occurs.

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

Definition at line 464 of file SGObject.cpp.

void set ( const Tag< T > &  _tag,
const T &  value 
)
inherited

Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 337 of file SGObject.h.

void set ( const std::string &  name,
const T &  value 
)
inherited

Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 363 of file SGObject.h.

bool set_alpha ( int32_t  idx,
float64_t  val 
)
inherited

set alpha at given index to given value

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

Definition at line 159 of file KernelMachine.cpp.

void set_alphas ( SGVector< float64_t >  alphas)
inherited

set alphas to given values

Parameters
alphasfloat vector with all alphas to set

Definition at line 174 of file KernelMachine.cpp.

void set_batch_computation_enabled ( bool  enable)
inherited

set batch computation enabled

Parameters
enableif batch computation shall be enabled

Definition at line 94 of file KernelMachine.cpp.

void set_bias ( float64_t  bias)
inherited

set bias to given value

Parameters
biasnew bias

Definition at line 129 of file KernelMachine.cpp.

void set_bias_enabled ( bool  enable_bias)
inherited

set state of bias

Parameters
enable_biasif bias shall be enabled

Definition at line 114 of file KernelMachine.cpp.

void set_C ( float64_t  c_neg,
float64_t  c_pos 
)
inherited

set C

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

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

Definition at line 118 of file SVM.h.

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

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

Parameters
mpointer to mkl object
cbcallback function

Definition at line 227 of file SVM.cpp.

void set_defaults ( int32_t  num_sv = 0)
inherited

set default values for members a SVM object

Definition at line 44 of file SVM.cpp.

void set_epsilon ( float64_t  eps)
inherited

set epsilon

Parameters
epsnew epsilon

Definition at line 125 of file SVM.h.

void set_generic ( )
inherited

Definition at line 74 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 79 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 84 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 89 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 94 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 99 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 104 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 109 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 114 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 119 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 124 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 129 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 134 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 139 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 144 of file SGObject.cpp.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO *  io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 261 of file SGObject.cpp.

void set_global_parallel ( Parallel *  parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 274 of file SGObject.cpp.

void set_global_version ( Version *  version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 316 of file SGObject.cpp.

void set_kernel ( CKernel *  k)
inherited

set kernel

Parameters
kkernel

Definition at line 81 of file KernelMachine.cpp.

void set_labels ( CLabels *  lab)
virtualinherited

set labels

Parameters
lablabels

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

Definition at line 65 of file Machine.cpp.

void set_linadd_enabled ( bool  enable)
inherited

set linadd enabled

Parameters
enableif linadd shall be enabled

Definition at line 104 of file KernelMachine.cpp.

void set_linear_term ( const SGVector< float64_t >  linear_term)
virtualinherited

set linear term of the QP

Parameters
linear_termthe linear term

Definition at line 309 of file SVM.cpp.

void set_loaded_status ( bool  loaded)
inherited

set svm loaded status

if svm been loaded

Definition at line 233 of file SVM.h.

void set_max_train_time ( float64_t  t)
inherited

set maximum training time

Parameters
tmaximimum training time

Definition at line 82 of file Machine.cpp.

void set_nu ( float64_t  nue)
inherited

set nu

Parameters
nuenew nu

Definition at line 107 of file SVM.h.

void set_objective ( float64_t  v)
inherited

set objective

Parameters
vobjective

Definition at line 209 of file SVM.h.

void set_qpsize ( int32_t  qps)
inherited

set qpsize

Parameters
qpsnew qpsize

Definition at line 143 of file SVM.h.

void set_shrinking_enabled ( bool  enable)
inherited

set state of shrinking

Parameters
enableif shrinking will be enabled

Definition at line 179 of file SVM.h.

void set_solver_type ( ESolverType  st)
inherited

set solver type

Parameters
stsolver type

Definition at line 97 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 107 of file Machine.cpp.

bool set_support_vector ( int32_t  idx,
int32_t  val 
)
inherited

set support vector at given index to given value

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

Definition at line 149 of file KernelMachine.cpp.

void set_support_vectors ( SGVector< int32_t >  svs)
inherited

set support vectors to given values

Parameters
svsinteger vector with all support vectors indexes to set

Definition at line 179 of file KernelMachine.cpp.

void set_tube_epsilon ( float64_t  eps)
inherited

set tube epsilon

Parameters
epsnew tube epsilon

Definition at line 131 of file SVM.h.

CSGObject * shallow_copy ( ) const
virtualinherited

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

Reimplemented in CGaussianKernel.

Definition at line 225 of file SGObject.cpp.

void store_model_features ( )
protectedvirtualinherited

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

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

Reimplemented from CMachine.

Definition at line 458 of file KernelMachine.cpp.

bool supports_locking ( ) const
virtualinherited
Returns
whether machine supports locking

Reimplemented from CMachine.

Definition at line 709 of file KernelMachine.cpp.

bool train ( CFeatures *  data = NULL)
virtualinherited

train machine

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

Reimplemented in CRelaxedTree, CAutoencoder, CLinearMachine, CSGDQN, and COnlineSVMSGD.

Definition at line 39 of file Machine.cpp.

bool train_locked ( SGVector< index_t >  indices)
virtualinherited

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

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

Reimplemented from CMachine.

Definition at line 487 of file KernelMachine.cpp.

bool train_machine ( CFeatures *  data = NULL)
protectedvirtual

train SVM

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 31 of file LibSVMOneClass.cpp.

virtual bool train_require_labels ( ) const
protectedvirtual

returns whether machine require labels for training

Reimplemented from CMachine.

Definition at line 50 of file LibSVMOneClass.h.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 336 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 281 of file SGObject.cpp.

Member Data Documentation

float64_t C1
protectedinherited

C1 regularization const

Definition at line 272 of file SVM.h.

float64_t C2
protectedinherited

C2

Definition at line 274 of file SVM.h.

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

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

Definition at line 284 of file SVM.h.

float64_t epsilon
protectedinherited

epsilon

Definition at line 266 of file SVM.h.

SGIO* io
inherited

io

Definition at line 558 of file SGObject.h.

CKernel* kernel
protectedinherited

kernel

Definition at line 314 of file KernelMachine.h.

SGVector<float64_t> m_alpha
protectedinherited

coefficients alpha

Definition at line 335 of file KernelMachine.h.

float64_t m_bias
protectedinherited

bias term b

Definition at line 332 of file KernelMachine.h.

CCustomKernel* m_custom_kernel
protectedinherited

is filled with pre-computed custom kernel on data lock

Definition at line 317 of file KernelMachine.h.

bool m_data_locked
protectedinherited

whether data is locked

Definition at line 374 of file Machine.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 573 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 576 of file SGObject.h.

CKernel* m_kernel_backup
protectedinherited

old kernel is stored here on data lock

Definition at line 320 of file KernelMachine.h.

CLabels* m_labels
protectedinherited

labels

Definition at line 365 of file Machine.h.

SGVector<float64_t> m_linear_term
protectedinherited

linear term in qp

Definition at line 261 of file SVM.h.

float64_t m_max_train_time
protectedinherited

maximum training time

Definition at line 362 of file Machine.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 570 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 567 of file SGObject.h.

ESolverType m_solver_type
protectedinherited

solver type

Definition at line 368 of file Machine.h.

bool m_store_model_features
protectedinherited

whether model features should be stored after training

Definition at line 371 of file Machine.h.

SGVector<int32_t> m_svs
protectedinherited

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

Definition at line 338 of file KernelMachine.h.

CMKL* mkl
protectedinherited

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

Definition at line 287 of file SVM.h.

float64_t nu
protectedinherited

nu

Definition at line 270 of file SVM.h.

float64_t objective
protectedinherited

objective

Definition at line 276 of file SVM.h.

Parallel* parallel
inherited

parallel

Definition at line 561 of file SGObject.h.

int32_t qpsize
protectedinherited

qpsize

Definition at line 278 of file SVM.h.

bool svm_loaded
protectedinherited

if SVM is loaded

Definition at line 264 of file SVM.h.

float64_t tube_epsilon
protectedinherited

tube epsilon for support vector regression

Definition at line 268 of file SVM.h.

bool use_batch_computation
protectedinherited

if batch computation is enabled

Definition at line 323 of file KernelMachine.h.

bool use_bias
protectedinherited

if bias shall be used

Definition at line 329 of file KernelMachine.h.

bool use_linadd
protectedinherited

if linadd is enabled

Definition at line 326 of file KernelMachine.h.

bool use_shrinking
protectedinherited

if shrinking shall be used

Definition at line 280 of file SVM.h.

Version* version
inherited

version

Definition at line 564 of file SGObject.h.

The documentation for this class was generated from the following files:
SHOGUN Machine Learning Toolbox - Documentation