Classifier Parameters. More...
#include <ClassifierKMeansStrategy.h>
Public Member Functions | |
AbstractParameters * | clone () const |
Create a clone copy of this instance. More... | |
const Parameters & | operator= (const Parameters ¶ms) |
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 | |
double | m_epsilon |
The stop criteria. When the clusters change in a value smaller then epsilon, the convergence is achieved. More... | |
unsigned int | m_K |
The number of clusters (means) to detect in image. 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 to perform if convergence is not achieved. More... | |
Definition at line 61 of file ClassifierKMeansStrategy.h.
te::rp::ClassifierKMeansStrategy::Parameters::Parameters | ( | ) |
Definition at line 47 of file ClassifierKMeansStrategy.cpp.
References reset().
te::rp::ClassifierKMeansStrategy::Parameters::~Parameters | ( | ) |
Definition at line 52 of file ClassifierKMeansStrategy.cpp.
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virtual |
Create a clone copy of this instance.
Implements te::common::AbstractParameters.
Definition at line 76 of file ClassifierKMeansStrategy.cpp.
const te::rp::ClassifierKMeansStrategy::Parameters & te::rp::ClassifierKMeansStrategy::Parameters::operator= | ( | const Parameters & | params | ) |
Definition at line 56 of file ClassifierKMeansStrategy.cpp.
References m_epsilon, m_K, m_maxInputPoints, and m_maxIterations.
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virtual |
Clear all internal allocated resources and reset the parameters instance to its initial state.
Implements te::common::AbstractParameters.
Definition at line 68 of file ClassifierKMeansStrategy.cpp.
Referenced by Parameters().
double te::rp::ClassifierKMeansStrategy::Parameters::m_epsilon |
The stop criteria. When the clusters change in a value smaller then epsilon, the convergence is achieved.
Definition at line 68 of file ClassifierKMeansStrategy.h.
Referenced by te::rp::ClassifierKMeansStrategy::execute(), te::qt::widgets::ClassifierWizardPage::getInputParams(), te::rp::ClassifierKMeansStrategy::initialize(), and operator=().
unsigned int te::rp::ClassifierKMeansStrategy::Parameters::m_K |
The number of clusters (means) to detect in image.
Definition at line 65 of file ClassifierKMeansStrategy.h.
Referenced by te::rp::ClassifierKMeansStrategy::execute(), te::qt::widgets::ClassifierWizardPage::getInputParams(), te::rp::ClassifierKMeansStrategy::initialize(), and operator=().
unsigned int te::rp::ClassifierKMeansStrategy::Parameters::m_maxInputPoints |
The maximum number of points used to estimate the clusters (default = 1000).
Definition at line 67 of file ClassifierKMeansStrategy.h.
Referenced by te::rp::ClassifierKMeansStrategy::execute(), te::qt::widgets::ClassifierWizardPage::getInputParams(), te::rp::ClassifierKMeansStrategy::initialize(), and operator=().
unsigned int te::rp::ClassifierKMeansStrategy::Parameters::m_maxIterations |
The maximum of iterations to perform if convergence is not achieved.
Definition at line 66 of file ClassifierKMeansStrategy.h.
Referenced by te::rp::ClassifierKMeansStrategy::execute(), te::qt::widgets::ClassifierWizardPage::getInputParams(), te::rp::ClassifierKMeansStrategy::initialize(), and operator=().