te::rp::ClassifierKMeansStrategy::Parameters Class Reference

Classifier Parameters. More...

#include <ClassifierKMeansStrategy.h>

Inheritance diagram for te::rp::ClassifierKMeansStrategy::Parameters:

Public Member Functions
AbstractParameters *	clone () const
	Create a clone copy of this instance. More...
const Parameters &	operator= (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
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...

Detailed Description

Classifier Parameters.

Definition at line 63 of file ClassifierKMeansStrategy.h.

Constructor & Destructor Documentation

Parameters()

te::rp::ClassifierKMeansStrategy::Parameters::Parameters

(

)

~Parameters()

te::rp::ClassifierKMeansStrategy::Parameters::~Parameters

(

)

Member Function Documentation

clone()

AbstractParameters* te::rp::ClassifierKMeansStrategy::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::ClassifierKMeansStrategy::Parameters::operator=

(

const Parameters &

params

)

reset()

void te::rp::ClassifierKMeansStrategy::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::ClassifierKMeansStrategy::Parameters::serialize ( AlgorithmParametersSerializer &  serializer ) const

virtual

Returns a parameter serialization object.

Parameters

serializer

The output serialization object.

Returns

Returns true if ok, false on erros.

Reimplemented from te::rp::ClassifierStrategyParameters.

Member Data Documentation

m_epsilon

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 70 of file ClassifierKMeansStrategy.h.

m_K

unsigned int te::rp::ClassifierKMeansStrategy::Parameters::m_K

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

Definition at line 67 of file ClassifierKMeansStrategy.h.

m_maxInputPoints

unsigned int te::rp::ClassifierKMeansStrategy::Parameters::m_maxInputPoints

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

Definition at line 69 of file ClassifierKMeansStrategy.h.

m_maxIterations

unsigned int te::rp::ClassifierKMeansStrategy::Parameters::m_maxIterations

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

Definition at line 68 of file ClassifierKMeansStrategy.h.

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

• /home/castejon/castejon_files/develop/terralib5/git_release/src/terralib/rp/ClassifierKMeansStrategy.h