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COnlineSVMSGD Class Reference

Detailed Description

class OnlineSVMSGD

Definition at line 33 of file OnlineSVMSGD.h.

Inheritance diagram for COnlineSVMSGD:
Inheritance graph
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Public Member Functions

 COnlineSVMSGD ()
 COnlineSVMSGD (float64_t C)
 COnlineSVMSGD (float64_t C, CStreamingDotFeatures *traindat)
virtual ~COnlineSVMSGD ()
virtual EClassifierType get_classifier_type ()
virtual bool train (CFeatures *data=NULL)
void set_C (float64_t c_neg, float64_t c_pos)
float64_t get_C1 ()
float64_t get_C2 ()
void set_epochs (int32_t e)
int32_t get_epochs ()
void set_lambda (float64_t l)
float64_t get_lambda ()
void set_bias_enabled (bool enable_bias)
bool get_bias_enabled ()
void set_regularized_bias_enabled (bool enable_bias)
bool get_regularized_bias_enabled ()
void set_loss_function (CLossFunction *loss_func)
CLossFunctionget_loss_function ()
virtual const char * get_name () const
- Public Member Functions inherited from COnlineLinearMachine
 COnlineLinearMachine ()
virtual ~COnlineLinearMachine ()
virtual void get_w (float32_t *&dst_w, int32_t &dst_dims)
virtual void get_w (float64_t *&dst_w, int32_t &dst_dims)
virtual SGVector< float32_tget_w ()
virtual void set_w (float32_t *src_w, int32_t src_w_dim)
virtual void set_w (float64_t *src_w, int32_t src_w_dim)
virtual void set_bias (float32_t b)
virtual float32_t get_bias ()
virtual bool load (FILE *srcfile)
virtual bool save (FILE *dstfile)
virtual void set_features (CStreamingDotFeatures *feat)
virtual CLabelsapply ()
virtual CLabelsapply (CFeatures *data)
virtual float64_t apply (int32_t vec_idx)
 get output for example "vec_idx"
virtual float32_t apply (float32_t *vec, int32_t len)
virtual float32_t apply_to_current_example ()
virtual CStreamingDotFeaturesget_features ()
- Public Member Functions inherited from CMachine
 CMachine ()
virtual ~CMachine ()
virtual void set_labels (CLabels *lab)
virtual CLabelsget_labels ()
virtual float64_t get_label (int32_t i)
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)
- Public Member Functions inherited from CSGObject
 CSGObject ()
 CSGObject (const CSGObject &orig)
virtual ~CSGObject ()
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="")
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 ()
SGVector< char * > get_modelsel_names ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)

Protected Member Functions

void calibrate (int32_t max_vec_num=1000)

Additional Inherited Members

- Public Attributes inherited from CSGObject
SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
- Protected Attributes inherited from COnlineLinearMachine
int32_t w_dim
float32_tw
float32_t bias
CStreamingDotFeaturesfeatures

Constructor & Destructor Documentation

default constructor

Definition at line 30 of file OnlineSVMSGD.cpp.

constructor

Parameters
Cconstant C

Definition at line 36 of file OnlineSVMSGD.cpp.

constructor

Parameters
Cconstant C
traindattraining features

Definition at line 45 of file OnlineSVMSGD.cpp.

~COnlineSVMSGD ( )
virtual

Definition at line 55 of file OnlineSVMSGD.cpp.

Member Function Documentation

void calibrate ( int32_t  max_vec_num = 1000)
protected

calibrate

Parameters
max_vec_numMaximum number of vectors to calibrate using (optional) if set to -1, tries to calibrate using all vectors

Definition at line 167 of file OnlineSVMSGD.cpp.

bool get_bias_enabled ( )

check if bias is enabled

Returns
if bias is enabled

Definition at line 124 of file OnlineSVMSGD.h.

float64_t get_C1 ( )

get C1

Returns
C1

Definition at line 82 of file OnlineSVMSGD.h.

float64_t get_C2 ( )

get C2

Returns
C2

Definition at line 88 of file OnlineSVMSGD.h.

virtual EClassifierType get_classifier_type ( )
virtual

get classifier type

Returns
classifier type OnlineSVMSGD

Reimplemented from CMachine.

Definition at line 58 of file OnlineSVMSGD.h.

int32_t get_epochs ( )

get epochs

Returns
the number of training epochs

Definition at line 100 of file OnlineSVMSGD.h.

float64_t get_lambda ( )

get lambda

Returns
the regularization parameter lambda

Definition at line 112 of file OnlineSVMSGD.h.

CLossFunction* get_loss_function ( )

Return the loss function

Returns
loss function as CLossFunction*

Definition at line 148 of file OnlineSVMSGD.h.

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

Reimplemented from COnlineLinearMachine.

Definition at line 151 of file OnlineSVMSGD.h.

bool get_regularized_bias_enabled ( )

check if regularized bias is enabled

Returns
if regularized bias is enabled

Definition at line 136 of file OnlineSVMSGD.h.

void set_bias_enabled ( bool  enable_bias)

set if bias shall be enabled

Parameters
enable_biasif bias shall be enabled

Definition at line 118 of file OnlineSVMSGD.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 76 of file OnlineSVMSGD.h.

void set_epochs ( int32_t  e)

set epochs

Parameters
enew number of training epochs

Definition at line 94 of file OnlineSVMSGD.h.

void set_lambda ( float64_t  l)

set lambda

Parameters
lvalue of regularization parameter lambda

Definition at line 106 of file OnlineSVMSGD.h.

void set_loss_function ( CLossFunction loss_func)

Set the loss function to use

Parameters
loss_funcobject derived from CLossFunction

Definition at line 60 of file OnlineSVMSGD.cpp.

void set_regularized_bias_enabled ( bool  enable_bias)

set if regularized bias shall be enabled

Parameters
enable_biasif regularized bias shall be enabled

Definition at line 130 of file OnlineSVMSGD.h.

bool train ( CFeatures data = NULL)
virtual

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 68 of file OnlineSVMSGD.cpp.


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

SHOGUN Machine Learning Toolbox - Documentation