te::rp::ClassifierMAPStrategy::Parameters Class Reference

Classifier Parameters. More...

#include <ClassifierMAPStrategy.h>

Inheritance diagram for te::rp::ClassifierMAPStrategy::Parameters:
te::rp::ClassifierStrategyParameters te::common::AbstractParameters

Public Types

typedef unsigned int ClassIDT
 Class ID type definition (zero means invalid ID). More...
 
typedef std::vector< ClassSampleTClassSamplesContainerT
 Class samples container type definition. More...
 
typedef std::vector< double > ClassSampleT
 Class sample type definition. More...
 
typedef std::map< ClassIDT, ClassSamplesContainerTMClassesSamplesCT
 Multi-classes samples container type definition. More...
 
typedef boost::shared_ptr< MClassesSamplesCTMClassesSamplesCTPtr
 A shared pointer to a multi classes samples container type definition. More...
 

Public Member Functions

AbstractParametersclone () const
 Create a clone copy of this instance. More...
 
const Parametersoperator= (const Parameters &params)
 
 Parameters ()
 
void reset ()
 Clear all internal allocated resources and reset the parameters instance to its initial state. More...
 
bool serialize (AlgorithmParametersSerializer &serializer) const
 Returns a parameter serialization object. More...
 
 ~Parameters ()
 

Public Attributes

te::cl::MAP::ModelParameters m_MAPModelParams
 Optional model parameters (further training not required). More...
 
unsigned int m_prioriCalcSampleStep
 A positive non-zero sample step used when calculating piori probabilities (default:5 - 1/5 of samples will be used);. More...
 
std::vector< double > m_prioriProbs
 Priori probabilities, one for each class. Values from 0 to 1 (use an empty vector to allow internal calcule of priori probabilities).
More...
 
MClassesSamplesCTPtr m_trainSamplesPtr
 A shared pointer to a always-valid structure where trainning samples are stored. More...
 

Detailed Description

Classifier Parameters.

Definition at line 62 of file ClassifierMAPStrategy.h.

Member Typedef Documentation

◆ ClassIDT

Class ID type definition (zero means invalid ID).

Definition at line 66 of file ClassifierMAPStrategy.h.

◆ ClassSamplesContainerT

Class samples container type definition.

Definition at line 70 of file ClassifierMAPStrategy.h.

◆ ClassSampleT

Class sample type definition.

Definition at line 68 of file ClassifierMAPStrategy.h.

◆ MClassesSamplesCT

Multi-classes samples container type definition.

Definition at line 72 of file ClassifierMAPStrategy.h.

◆ MClassesSamplesCTPtr

A shared pointer to a multi classes samples container type definition.

Definition at line 74 of file ClassifierMAPStrategy.h.

Constructor & Destructor Documentation

◆ Parameters()

te::rp::ClassifierMAPStrategy::Parameters::Parameters ( )

◆ ~Parameters()

te::rp::ClassifierMAPStrategy::Parameters::~Parameters ( )

Member Function Documentation

◆ clone()

AbstractParameters* te::rp::ClassifierMAPStrategy::Parameters::clone ( ) const
virtual

Create a clone copy of this instance.

Returns
A clone copy of this instance.
Note
The caller will take the ownership of the returned pointer.

Implements te::common::AbstractParameters.

◆ operator=()

const Parameters& te::rp::ClassifierMAPStrategy::Parameters::operator= ( const Parameters params)

◆ reset()

void te::rp::ClassifierMAPStrategy::Parameters::reset ( )
virtual

Clear all internal allocated resources and reset the parameters instance to its initial state.

Implements te::common::AbstractParameters.

◆ serialize()

bool te::rp::ClassifierMAPStrategy::Parameters::serialize ( AlgorithmParametersSerializer serializer) const
virtual

Returns a parameter serialization object.

Parameters
serializerThe output serialization object.
Returns
Returns true if ok, false on erros.

Reimplemented from te::rp::ClassifierStrategyParameters.

Member Data Documentation

◆ m_MAPModelParams

te::cl::MAP::ModelParameters te::rp::ClassifierMAPStrategy::Parameters::m_MAPModelParams

Optional model parameters (further training not required).

Definition at line 82 of file ClassifierMAPStrategy.h.

◆ m_prioriCalcSampleStep

unsigned int te::rp::ClassifierMAPStrategy::Parameters::m_prioriCalcSampleStep

A positive non-zero sample step used when calculating piori probabilities (default:5 - 1/5 of samples will be used);.

Definition at line 80 of file ClassifierMAPStrategy.h.

◆ m_prioriProbs

std::vector< double > te::rp::ClassifierMAPStrategy::Parameters::m_prioriProbs

Priori probabilities, one for each class. Values from 0 to 1 (use an empty vector to allow internal calcule of priori probabilities).

Definition at line 78 of file ClassifierMAPStrategy.h.

◆ m_trainSamplesPtr

MClassesSamplesCTPtr te::rp::ClassifierMAPStrategy::Parameters::m_trainSamplesPtr

A shared pointer to a always-valid structure where trainning samples are stored.

Definition at line 76 of file ClassifierMAPStrategy.h.


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