CPluginEstimate Class Reference

Inheritance diagram for CPluginEstimate:

Inheritance graph
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List of all members.

Public Member Functions

 CPluginEstimate (float64_t pos_pseudo=1e-10, float64_t neg_pseudo=1e-10)
virtual ~CPluginEstimate ()
bool train ()
CLabelsclassify (CLabels *output=NULL)
 classify all test features
virtual void set_features (CStringFeatures< uint16_t > *feat)
virtual CStringFeatures
< uint16_t > * 
get_features ()
float64_t classify_example (int32_t vec_idx)
 classify the test feature vector indexed by vec_idx
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 (const float64_t *pos_params, const float64_t *neg_params, int32_t seq_length, int32_t num_symbols)
int32_t get_num_params ()
bool check_models ()

Protected Attributes

float64_t m_pos_pseudo
float64_t m_neg_pseudo
CLinearHMMpos_model
CLinearHMMneg_model
CStringFeatures< uint16_t > * features


Detailed Description

class PluginEstimate

Definition at line 20 of file PluginEstimate.h.


Constructor & Destructor Documentation

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

default constructor

Parameters:
pos_pseudo pseudo for positive model
neg_pseudo pseudo for negative model

Definition at line 19 of file PluginEstimate.cpp.

CPluginEstimate::~CPluginEstimate (  )  [virtual]

Definition at line 25 of file PluginEstimate.cpp.


Member Function Documentation

bool CPluginEstimate::check_models (  ) 

check models

Returns:
if one of the two models is invalid

Definition at line 173 of file PluginEstimate.h.

CLabels * CPluginEstimate::classify ( CLabels output = NULL  )  [virtual]

classify all test features

Reimplemented from CClassifier.

Definition at line 70 of file PluginEstimate.cpp.

float64_t CPluginEstimate::classify_example ( int32_t  vec_idx  )  [virtual]

classify the test feature vector indexed by vec_idx

Reimplemented from CClassifier.

Definition at line 84 of file PluginEstimate.cpp.

virtual CStringFeatures<uint16_t>* CPluginEstimate::get_features (  )  [virtual]

get features

Returns:
features

Definition at line 54 of file PluginEstimate.h.

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

get model parameters

Parameters:
pos_params parameters of positive model
neg_params parameters of negative model
seq_length sequence length
num_symbols numbe of symbols
Returns:
if operation was successful

Definition at line 113 of file PluginEstimate.h.

int32_t CPluginEstimate::get_num_params (  ) 

get number of parameters

Returns:
number of parameters

Definition at line 164 of file PluginEstimate.h.

float64_t CPluginEstimate::get_parameterwise_log_odds ( uint16_t  obs,
int32_t  position 
)

get log odds parameter-wise

Parameters:
obs observation
position position
Returns:
log odd at position

Definition at line 77 of file PluginEstimate.h.

float64_t CPluginEstimate::log_derivative_neg_obsolete ( uint16_t  obs,
int32_t  pos 
)

get obsolete negative log derivative

Parameters:
obs observation
pos position
Returns:
negative log derivative

Definition at line 100 of file PluginEstimate.h.

float64_t CPluginEstimate::log_derivative_pos_obsolete ( uint16_t  obs,
int32_t  pos 
)

get obsolete positive log derivative

Parameters:
obs observation
pos position
Returns:
positive log derivative

Definition at line 89 of file PluginEstimate.h.

float64_t CPluginEstimate::posterior_log_odds_obsolete ( uint16_t *  vector,
int32_t  len 
)

obsolete posterior log odds

Parameters:
vector vector
len len
Returns:
something floaty

Definition at line 65 of file PluginEstimate.h.

virtual void CPluginEstimate::set_features ( CStringFeatures< uint16_t > *  feat  )  [virtual]

set features

Parameters:
feat features to set

Definition at line 43 of file PluginEstimate.h.

void CPluginEstimate::set_model_params ( const float64_t pos_params,
const float64_t neg_params,
int32_t  seq_length,
int32_t  num_symbols 
)

set model parameters

Parameters:
pos_params parameters of positive model
neg_params parameters of negative model
seq_length sequence length
num_symbols numbe of symbols

Definition at line 141 of file PluginEstimate.h.

bool CPluginEstimate::train (  )  [virtual]

train the estimate

Returns:
if training was successful

Reimplemented from CClassifier.

Definition at line 33 of file PluginEstimate.cpp.


Member Data Documentation

features

Definition at line 190 of file PluginEstimate.h.

pseudo count for negative class

Definition at line 182 of file PluginEstimate.h.

pseudo count for positive class

Definition at line 180 of file PluginEstimate.h.

negative model

Definition at line 187 of file PluginEstimate.h.

positive model

Definition at line 185 of file PluginEstimate.h.


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

SHOGUN Machine Learning Toolbox - Documentation