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CPluginEstimate Class Reference

Detailed Description

class PluginEstimate

The class PluginEstimate takes as input two probabilistic models (of type CLinearHMM, even though general models are possible ) and classifies examples according to the rule

\[ f({\bf x})= \log(\mbox{Pr}({\bf x}|\theta_+)) - \log(\mbox{Pr}({\bf x}|\theta_-)) \]

See Also
CLinearHMM
CDistribution

Definition at line 34 of file PluginEstimate.h.

Inheritance diagram for CPluginEstimate:
Inheritance graph
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Public Member Functions

 CPluginEstimate (float64_t pos_pseudo=1e-10, float64_t neg_pseudo=1e-10)
 
virtual ~CPluginEstimate ()
 
CLabels * apply ()
 
virtual CLabels * apply (CFeatures *data)
 
virtual void set_features (CStringFeatures< uint16_t > *feat)
 
virtual CStringFeatures
< uint16_t > * 		get_features ()
 
float64_t apply (int32_t vec_idx)
 classify the test feature vector indexed by vec_idx More...
 
float64_t posterior_log_odds_obsolete (uint16_t *vector, int32_t len)
 
float64_t get_parameterwise_log_odds (uint16_t obs, int32_t position)
 
float64_t log_derivative_pos_obsolete (uint16_t obs, int32_t pos)
 
float64_t log_derivative_neg_obsolete (uint16_t obs, int32_t pos)
 
bool get_model_params (float64_t *&pos_params, float64_t *&neg_params, int32_t &seq_length, int32_t &num_symbols)
 
void set_model_params (float64_t *pos_params, float64_t *neg_params, int32_t seq_length, int32_t num_symbols)
 
int32_t get_num_params ()
 
bool check_models ()
 
virtual const char * get_name () const
 
- Public Member Functions inherited from CMachine
 CMachine ()
 
virtual ~CMachine ()
 
virtual bool train (CFeatures *data=NULL)
 
virtual bool load (FILE *srcfile)
 
virtual bool save (FILE *dstfile)
 
virtual void set_labels (CLabels *lab)
 
virtual CLabels * get_labels ()
 
virtual float64_t get_label (int32_t i)
 
void set_max_train_time (float64_t t)
 
float64_t get_max_train_time ()
 
virtual EClassifierType get_classifier_type ()
 
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)
 
SGIO * get_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallel * get_global_parallel ()
 
void set_global_version (Version *version)
 
Version * get_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)
 
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 ()
 

Protected Member Functions

virtual bool train_machine (CFeatures *data=NULL)
 
- Protected Member Functions inherited from CMachine
virtual void store_model_features ()
 
- Protected Member Functions inherited from CSGObject
virtual void load_serializable_pre () throw (ShogunException)
 
virtual void load_serializable_post () throw (ShogunException)
 
virtual void save_serializable_pre () throw (ShogunException)
 
virtual void save_serializable_post () throw (ShogunException)
 

Protected Attributes

float64_t m_pos_pseudo
 
float64_t m_neg_pseudo
 
CLinearHMM * pos_model
 
CLinearHMM * neg_model
 
CStringFeatures< uint16_t > * features
 
- Protected Attributes inherited from CMachine
float64_t max_train_time
 
CLabels * labels
 
ESolverType solver_type
 
bool m_store_model_features
 

Additional Inherited Members

- Public Attributes inherited from CSGObject
SGIO * io
 
Parallel * parallel
 
Version * version
 
Parameter * m_parameters
 
Parameter * m_model_selection_parameters
 

Constructor & Destructor Documentation

CPluginEstimate ( float64_t  pos_pseudo = 1e-10,
float64_t  neg_pseudo = 1e-10 
)

default constructor

Parameters
pos_pseudopseudo for positive model
neg_pseudopseudo for negative model

Definition at line 20 of file PluginEstimate.cpp.

~CPluginEstimate ( )
virtual

Definition at line 38 of file PluginEstimate.cpp.

Member Function Documentation

CLabels * apply ( )
virtual

classify objects using the currently set features

Returns
classified labels

Implements CMachine.

Definition at line 96 of file PluginEstimate.cpp.

CLabels * apply ( CFeatures *  data)
virtual

classify objects

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

Implements CMachine.

Definition at line 108 of file PluginEstimate.cpp.

float64_t apply ( int32_t  vec_idx)
virtual

classify the test feature vector indexed by vec_idx

Reimplemented from CMachine.

Definition at line 123 of file PluginEstimate.cpp.

bool check_models ( )

check models

Returns
if one of the two models is invalid

Definition at line 195 of file PluginEstimate.h.

virtual CStringFeatures<uint16_t>* get_features ( )
virtual

get features

Returns
features

Definition at line 72 of file PluginEstimate.h.

bool get_model_params ( float64_t *&  pos_params,
float64_t *&  neg_params,
int32_t &  seq_length,
int32_t &  num_symbols 
)

get model parameters

Parameters
pos_paramsparameters of positive model
neg_paramsparameters of negative model
seq_lengthsequence length
num_symbolsnumbe of symbols
Returns
if operation was successful

Definition at line 131 of file PluginEstimate.h.

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

Implements CSGObject.

Definition at line 201 of file PluginEstimate.h.

int32_t get_num_params ( )

get number of parameters

Returns
number of parameters

Definition at line 186 of file PluginEstimate.h.

float64_t get_parameterwise_log_odds ( uint16_t  obs,
int32_t  position 
)

get log odds parameter-wise

Parameters
obsobservation
positionposition
Returns
log odd at position

Definition at line 95 of file PluginEstimate.h.

float64_t log_derivative_neg_obsolete ( uint16_t  obs,
int32_t  pos 
)

get obsolete negative log derivative

Parameters
obsobservation
posposition
Returns
negative log derivative

Definition at line 118 of file PluginEstimate.h.

float64_t log_derivative_pos_obsolete ( uint16_t  obs,
int32_t  pos 
)

get obsolete positive log derivative

Parameters
obsobservation
posposition
Returns
positive log derivative

Definition at line 107 of file PluginEstimate.h.

float64_t posterior_log_odds_obsolete ( uint16_t *  vector,
int32_t  len 
)

obsolete posterior log odds

Parameters
vectorvector
lenlen
Returns
something floaty

Definition at line 83 of file PluginEstimate.h.

virtual void set_features ( CStringFeatures< uint16_t > *  feat)
virtual

set features

Parameters
featfeatures to set

Definition at line 61 of file PluginEstimate.h.

void set_model_params ( float64_t *  pos_params,
float64_t *  neg_params,
int32_t  seq_length,
int32_t  num_symbols 
)

set model parameters

Parameters
pos_paramsparameters of positive model
neg_paramsparameters of negative model
seq_lengthsequence length
num_symbolsnumbe of symbols

Definition at line 159 of file PluginEstimate.h.

bool train_machine ( CFeatures *  data = NULL)
protectedvirtual

train plugin estimate 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 46 of file PluginEstimate.cpp.

Member Data Documentation

CStringFeatures<uint16_t>* features
protected

features

Definition at line 226 of file PluginEstimate.h.

float64_t m_neg_pseudo
protected

pseudo count for negative class

Definition at line 218 of file PluginEstimate.h.

float64_t m_pos_pseudo
protected

pseudo count for positive class

Definition at line 216 of file PluginEstimate.h.

CLinearHMM* neg_model
protected

negative model

Definition at line 223 of file PluginEstimate.h.

CLinearHMM* pos_model
protected

positive model

Definition at line 221 of file PluginEstimate.h.

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