Public Member Functions | Public Attributes | List of all members
te::rp::ClassifierEMStrategy::Parameters Class Reference

Classifier Parameters. More...

#include <ClassifierEMStrategy.h>

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

Public Member Functions

AbstractParameters * clone () const
 Create a clone copy of this instance. More...
 
const Parameters & operator= (const Parameters &params)
 
 Parameters ()
 
void reset () throw ( te::rp::Exception )
 Clear all internal allocated resources and reset the parameters instance to its initial state. More...
 
 ~Parameters ()
 

Public Attributes

std::vector< std::vector< double > > m_clustersMeans
 The previously estimated means of the clusters (optional). More...
 
double m_epsilon
 The stop criteria. When the clusters change in a value smaller then epsilon, the convergence is achieved. More...
 
unsigned int m_maxInputPoints
 The maximum number of points used to estimate the clusters (default = 1000). More...
 
unsigned int m_maxIterations
 The maximum of iterations (E/M steps) to perform if convergence is not achieved. More...
 
unsigned int m_numberOfClusters
 The number of clusters (classes) to estimate in the image. More...
 

Detailed Description

Classifier Parameters.

Definition at line 67 of file ClassifierEMStrategy.h.

Constructor & Destructor Documentation

te::rp::ClassifierEMStrategy::Parameters::Parameters ( )
te::rp::ClassifierEMStrategy::Parameters::~Parameters ( )

Member Function Documentation

AbstractParameters* te::rp::ClassifierEMStrategy::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.

const Parameters& te::rp::ClassifierEMStrategy::Parameters::operator= ( const Parameters &  params)
void te::rp::ClassifierEMStrategy::Parameters::reset ( )
throw (te::rp::Exception
)
virtual

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

Implements te::common::AbstractParameters.

Member Data Documentation

std::vector<std::vector<double> > te::rp::ClassifierEMStrategy::Parameters::m_clustersMeans

The previously estimated means of the clusters (optional).

Definition at line 75 of file ClassifierEMStrategy.h.

double te::rp::ClassifierEMStrategy::Parameters::m_epsilon

The stop criteria. When the clusters change in a value smaller then epsilon, the convergence is achieved.

Definition at line 74 of file ClassifierEMStrategy.h.

unsigned int te::rp::ClassifierEMStrategy::Parameters::m_maxInputPoints

The maximum number of points used to estimate the clusters (default = 1000).

Definition at line 73 of file ClassifierEMStrategy.h.

unsigned int te::rp::ClassifierEMStrategy::Parameters::m_maxIterations

The maximum of iterations (E/M steps) to perform if convergence is not achieved.

Definition at line 72 of file ClassifierEMStrategy.h.

unsigned int te::rp::ClassifierEMStrategy::Parameters::m_numberOfClusters

The number of clusters (classes) to estimate in the image.

Definition at line 71 of file ClassifierEMStrategy.h.

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