te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters Class Reference

Classifier Parameters. More...

#include <KMeans.h>

Inheritance diagram for te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters:

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::cl::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_maxIterations
	The maximum of iterations to perform if convergence is not achieved. More...

Detailed Description

template<class TTRAIN, class TCLASSIFY>
class te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters

Classifier Parameters.

Definition at line 71 of file KMeans.h.

Constructor & Destructor Documentation

template<class TTRAIN , class TCLASSIFY >

te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::Parameters

(

)

Definition at line 125 of file KMeans.h.

References te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::reset().

template<class TTRAIN , class TCLASSIFY >

te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::~Parameters

(

)

Definition at line 131 of file KMeans.h.

Member Function Documentation

template<class TTRAIN , class TCLASSIFY >

te::common::AbstractParameters * te::cl::KMeans< TTRAIN, TCLASSIFY >::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.

Definition at line 156 of file KMeans.h.

template<class TTRAIN , class TCLASSIFY >

const te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters & te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::operator=

(

const Parameters &

params

)

Definition at line 136 of file KMeans.h.

References te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::m_epsilon, te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::m_K, te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::m_maxIterations, and te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::reset().

template<class TTRAIN , class TCLASSIFY >

void te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::reset ( ) throw ( te::cl::Exception )

virtual

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

Implements te::common::AbstractParameters.

Definition at line 148 of file KMeans.h.

Referenced by te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::operator=(), and te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::Parameters().

Member Data Documentation

template<class TTRAIN , class TCLASSIFY >

double te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::m_epsilon

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

Definition at line 77 of file KMeans.h.

Referenced by te::cl::KMeans< TTRAIN, TCLASSIFY >::initialize(), te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::operator=(), and te::cl::KMeans< TTRAIN, TCLASSIFY >::train().

template<class TTRAIN , class TCLASSIFY >

unsigned int te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::m_K

The number of clusters (means) to detect in image.

Definition at line 75 of file KMeans.h.

Referenced by te::cl::KMeans< TTRAIN, TCLASSIFY >::getClassification(), te::cl::KMeans< TTRAIN, TCLASSIFY >::initialize(), te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::operator=(), and te::cl::KMeans< TTRAIN, TCLASSIFY >::train().

template<class TTRAIN , class TCLASSIFY >

unsigned int te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::m_maxIterations

The maximum of iterations to perform if convergence is not achieved.

Definition at line 76 of file KMeans.h.

Referenced by te::cl::KMeans< TTRAIN, TCLASSIFY >::initialize(), te::cl::KMeans< TTRAIN, TCLASSIFY >::Parameters::operator=(), and te::cl::KMeans< TTRAIN, TCLASSIFY >::train().

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

• C:/CC_master/terralib5/src/terralib/classification/KMeans.h