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CKernelMachine Class Reference

Detailed Description

A generic KernelMachine interface.

A kernel machine is defined as

\[ f({\bf x})=\sum_{i=0}^{N-1} \alpha_i k({\bf x}, {\bf x_i})+b \]

where \(N\) is the number of training examples \(\alpha_i\) are the weights assigned to each training example \(k(x,x')\) is the kernel and \(b\) the bias.

Using an a-priori choosen kernel, the \(\alpha_i\) and bias are determined in a training procedure.

Kernel machines support locking. This means that given some data, the machine can be locked. When this is done, the kernel matrix is computed and stored in a custom kernel. Speeds up cross-validation. Only train_locked and apply_locked are available when locked.

Definition at line 51 of file KernelMachine.h.

Inheritance diagram for CKernelMachine:
[legend]

Public Member Functions

 CKernelMachine ()
 
 CKernelMachine (CKernel *k, const SGVector< float64_t > alphas, const SGVector< int32_t > svs, float64_t b)
 
 CKernelMachine (CKernelMachine *machine)
 
virtual ~CKernelMachine ()
 
virtual const char * get_name () const
 
void set_kernel (CKernel *k)
 
CKernelget_kernel ()
 
void set_batch_computation_enabled (bool enable)
 
bool get_batch_computation_enabled ()
 
void set_linadd_enabled (bool enable)
 
bool get_linadd_enabled ()
 
void set_bias_enabled (bool enable_bias)
 
bool get_bias_enabled ()
 
float64_t get_bias ()
 
void set_bias (float64_t bias)
 
int32_t get_support_vector (int32_t idx)
 
float64_t get_alpha (int32_t idx)
 
bool set_support_vector (int32_t idx, int32_t val)
 
bool set_alpha (int32_t idx, float64_t val)
 
int32_t get_num_support_vectors ()
 
void set_alphas (SGVector< float64_t > alphas)
 
void set_support_vectors (SGVector< int32_t > svs)
 
SGVector< int32_t > get_support_vectors ()
 
SGVector< float64_tget_alphas ()
 
bool create_new_model (int32_t num)
 
bool init_kernel_optimization ()
 
virtual CRegressionLabelsapply_regression (CFeatures *data=NULL)
 
virtual CBinaryLabelsapply_binary (CFeatures *data=NULL)
 
virtual float64_t apply_one (int32_t num)
 
virtual bool train_locked (SGVector< index_t > indices)
 
virtual CBinaryLabelsapply_locked_binary (SGVector< index_t > indices)
 
virtual CRegressionLabelsapply_locked_regression (SGVector< index_t > indices)
 
virtual SGVector< float64_tapply_locked_get_output (SGVector< index_t > indices)
 
virtual void data_lock (CLabels *labs, CFeatures *features=NULL)
 
virtual void data_unlock ()
 
virtual bool supports_locking () const
 
virtual bool train (CFeatures *data=NULL)
 
virtual CLabelsapply (CFeatures *data=NULL)
 
virtual CMulticlassLabelsapply_multiclass (CFeatures *data=NULL)
 
virtual CStructuredLabelsapply_structured (CFeatures *data=NULL)
 
virtual CLatentLabelsapply_latent (CFeatures *data=NULL)
 
virtual void set_labels (CLabels *lab)
 
virtual CLabelsget_labels ()
 
void set_max_train_time (float64_t t)
 
float64_t get_max_train_time ()
 
virtual EMachineType get_classifier_type ()
 
void set_solver_type (ESolverType st)
 
ESolverType get_solver_type ()
 
virtual void set_store_model_features (bool store_model)
 
virtual CLabelsapply_locked (SGVector< index_t > indices)
 
virtual CMulticlassLabelsapply_locked_multiclass (SGVector< index_t > indices)
 
virtual CStructuredLabelsapply_locked_structured (SGVector< index_t > indices)
 
virtual CLatentLabelsapply_locked_latent (SGVector< index_t > indices)
 
virtual void post_lock (CLabels *labs, CFeatures *features)
 
bool is_data_locked () const
 
virtual EProblemType get_machine_problem_type () const
 
virtual CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
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)
 
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)
 
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 >
get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
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 CSGObjectclone ()
 

Static Public Member Functions

static void * apply_helper (void *p)
 

Public Attributes

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

SGVector< float64_tapply_get_outputs (CFeatures *data)
 
virtual void store_model_features ()
 
virtual bool train_machine (CFeatures *data=NULL)
 
virtual bool is_label_valid (CLabels *lab) const
 
virtual bool train_require_labels () 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)
 

Protected Attributes

CKernelkernel
 
CCustomKernelm_custom_kernel
 
CKernelm_kernel_backup
 
bool use_batch_computation
 
bool use_linadd
 
bool use_bias
 
float64_t m_bias
 
SGVector< float64_tm_alpha
 
SGVector< int32_t > m_svs
 
float64_t m_max_train_time
 
CLabelsm_labels
 
ESolverType m_solver_type
 
bool m_store_model_features
 
bool m_data_locked
 

Constructor & Destructor Documentation

default constructor

Definition at line 38 of file KernelMachine.cpp.

CKernelMachine ( CKernel k,
const SGVector< float64_t alphas,
const SGVector< int32_t >  svs,
float64_t  b 
)

Convenience constructor to initialize a trained kernel machine

Parameters
kkernel
alphasvector of alpha weights
svsindices of examples, i.e. i's for x_i
bbias term

Definition at line 43 of file KernelMachine.cpp.

copy constructor

Parameters
machinemachine having parameters to copy

Definition at line 57 of file KernelMachine.cpp.

~CKernelMachine ( )
virtual

destructor

Definition at line 74 of file KernelMachine.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)
virtual

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)
protected

apply get outputs

Parameters
datafeatures to compute outputs
Returns
outputs

Definition at line 254 of file KernelMachine.cpp.

void * apply_helper ( void *  p)
static

apply example helper, used in threads

Parameters
pparams of the thread
Returns
nothing really

Definition at line 424 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)
virtual

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 518 of file KernelMachine.cpp.

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

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 531 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)
virtual

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 524 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
float64_t apply_one ( int32_t  num)
virtual

apply kernel machine to one example

Parameters
numwhich example to apply to
Returns
classified value

Reimplemented from CMachine.

Definition at line 405 of file KernelMachine.cpp.

CRegressionLabels * apply_regression ( CFeatures data = NULL)
virtual

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

Definition at line 747 of file SGObject.cpp.

bool create_new_model ( int32_t  num)

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 
)
virtual

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 623 of file KernelMachine.cpp.

void data_unlock ( )
virtual

Unlocks a locked machine and restores previous state

Reimplemented from CMachine.

Definition at line 654 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 367 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 388 of file SGObject.h.

float64_t get_alpha ( int32_t  idx)

get alpha at given index

Parameters
idxindex of alpha
Returns
alpha

Definition at line 140 of file KernelMachine.cpp.

SGVector< float64_t > get_alphas ( )
Returns
vector of alphas

Definition at line 189 of file KernelMachine.cpp.

bool get_batch_computation_enabled ( )

check if batch computation is enabled

Returns
if batch computation is enabled

Definition at line 99 of file KernelMachine.cpp.

float64_t get_bias ( )

get bias

Returns
bias

Definition at line 124 of file KernelMachine.cpp.

bool get_bias_enabled ( )

get state of bias

Returns
state of bias

Definition at line 119 of file KernelMachine.cpp.

EMachineType get_classifier_type ( )
virtualinherited
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 ( )

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 ( )

check if linadd is enabled

Returns
if linadd is enabled

Definition at line 109 of file KernelMachine.cpp.

virtual EProblemType get_machine_problem_type ( ) const
virtualinherited

returns type of problem machine solves

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

Definition at line 299 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 the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.

Returns
name of the SGSerializable

Reimplemented from CMachine.

Reimplemented in CSVMLight, CMKL, CSVM, CSVRLight, CKernelRidgeRegression, CKRRNystrom, CLibSVR, CDomainAdaptationSVM, CLibSVM, CSVMLightOneClass, CMKLRegression, CMKLOneClass, CLibSVMOneClass, CMPDSVM, CMKLClassification, and CGNPPSVM.

Definition at line 80 of file KernelMachine.h.

int32_t get_num_support_vectors ( )

get number of support vectors

Returns
number of support vectors

Definition at line 169 of file KernelMachine.cpp.

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)

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 ( )
Returns
all support vectors

Definition at line 184 of file KernelMachine.cpp.

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 289 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 301 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 312 of file SGObject.h.

bool init_kernel_optimization ( )

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 296 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 348 of file Machine.h.

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.

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 287 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 439 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 452 of file SGObject.h.

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 328 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 354 of file SGObject.h.

bool set_alpha ( int32_t  idx,
float64_t  val 
)

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)

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)

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)

set bias to given value

Parameters
biasnew bias

Definition at line 129 of file KernelMachine.cpp.

void set_bias_enabled ( bool  enable_bias)

set state of bias

Parameters
enable_biasif bias shall be enabled

Definition at line 114 of file KernelMachine.cpp.

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)

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)

set linadd enabled

Parameters
enableif linadd shall be enabled

Definition at line 104 of file KernelMachine.cpp.

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_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 
)

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)

set support vectors to given values

Parameters
svsinteger vector with all support vectors indexes to set

Definition at line 179 of file KernelMachine.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 225 of file SGObject.cpp.

void store_model_features ( )
protectedvirtual

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 453 of file KernelMachine.cpp.

bool supports_locking ( ) const
virtual
Returns
whether machine supports locking

Reimplemented from CMachine.

Definition at line 699 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)
virtual

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 482 of file KernelMachine.cpp.

virtual bool train_machine ( CFeatures data = NULL)
protectedvirtualinherited
virtual bool train_require_labels ( ) const
protectedvirtualinherited

returns whether machine require labels for training

Reimplemented in COnlineLinearMachine, CKMeansBase, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree, and CLibSVMOneClass.

Definition at line 354 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 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

SGIO* io
inherited

io

Definition at line 537 of file SGObject.h.

CKernel* kernel
protected

kernel

Definition at line 311 of file KernelMachine.h.

SGVector<float64_t> m_alpha
protected

coefficients alpha

Definition at line 332 of file KernelMachine.h.

float64_t m_bias
protected

bias term b

Definition at line 329 of file KernelMachine.h.

CCustomKernel* m_custom_kernel
protected

is filled with pre-computed custom kernel on data lock

Definition at line 314 of file KernelMachine.h.

bool m_data_locked
protectedinherited

whether data is locked

Definition at line 370 of file Machine.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 552 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 555 of file SGObject.h.

CKernel* m_kernel_backup
protected

old kernel is stored here on data lock

Definition at line 317 of file KernelMachine.h.

CLabels* m_labels
protectedinherited

labels

Definition at line 361 of file Machine.h.

float64_t m_max_train_time
protectedinherited

maximum training time

Definition at line 358 of file Machine.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 549 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 546 of file SGObject.h.

ESolverType m_solver_type
protectedinherited

solver type

Definition at line 364 of file Machine.h.

bool m_store_model_features
protectedinherited

whether model features should be stored after training

Definition at line 367 of file Machine.h.

SGVector<int32_t> m_svs
protected

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

Definition at line 335 of file KernelMachine.h.

Parallel* parallel
inherited

parallel

Definition at line 540 of file SGObject.h.

bool use_batch_computation
protected

if batch computation is enabled

Definition at line 320 of file KernelMachine.h.

bool use_bias
protected

if bias shall be used

Definition at line 326 of file KernelMachine.h.

bool use_linadd
protected

if linadd is enabled

Definition at line 323 of file KernelMachine.h.

Version* version
inherited

version

Definition at line 543 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation