ipsdk::math::clustering::KernelKMeansClusteringConfig Class Reference

Public Member Functions
void	setNbAttempts (const ipUInt32 nbAttempts)
	set number of attempts for K-Means algorithm More...
ipUInt32	getNbAttempts () const
	retrieve number of attempts for K-Means algorithm More...
void	setNbMaxIteration (const ipUInt32 nbMaxIteration)
	set maximum number of K-Means algorithm iterations for an attempt More...
ipUInt32	getNbMaxIteration () const
void	setMinChangeRatio (const ipReal64 minChangeRatio)
	set minimum ratio for sample assignment change (versus full number of samples) to consider that an iteration has converged More...
ipReal64	getMinChangeRatio () const
void	setAccuracyThreshold (const ipReal64 accuracyThreshold)
	set accuracy threshold for approximate linear dependence condition More...
ipReal64	getAccuracyThreshold () const
	retrieve accuracy threshold for approximate linear dependence condition
void	setMaxDictionarySize (const ipUInt32 maxDictionarySize)
	set maximum dictionary size by cluster More...
ipUInt32	getMaxDictionarySize () const
	retrieve maximum dictionary size for processing
Constructors and destructor
	KernelKMeansClusteringConfig ()
	~KernelKMeansClusteringConfig ()

Static Public Member Functions
static ipUInt32	getDefaultNbAttempts ()
static ipUInt32	getDefaultMaxIteration ()
static ipReal64	getDefaultMinChangeRatio ()
	function allowing to retrieve default minimum ratio for sample assignment change (versus full number of samples) to consider that an iteration has converged
static ipReal64	getDefaultAccuracyThreshold ()
	function allowing to retrieve default accuracy threshold value for approximate linear dependence condition
static ipUInt32	getDefaultMaxDictionarySize ()
	function allowinf to retrieve default maximum dictionary size for processing

Protected Attributes
ipUInt32	_nbAttempts
	number of attempts for K-Means algorithm More...
ipUInt32	_nbMaxIteration
ipReal64	_minChangeRatio
ipReal64	_accuracyThreshold
	accuracy threshold value for approximate linear dependence condition
ipUInt32	_maxDictionarySize
	maximum dictionary size for processing

Member Function Documentation

getDefaultNbAttempts()

static ipUInt32 ipsdk::math::clustering::KernelKMeansClusteringConfig::getDefaultNbAttempts ( )

inlinestatic

function allowing to retrieve default number of attempts for K-Means algorithm

setNbAttempts()

void ipsdk::math::clustering::KernelKMeansClusteringConfig::setNbAttempts

(

const ipUInt32

nbAttempts

)

set number of attempts for K-Means algorithm

Each attempt is associated to a different initialization using K-Means++ algorithm.

Exceptions

ipsdk::math::IPSDKMathException

if nbAttempts == 0

getNbAttempts()

ipUInt32 ipsdk::math::clustering::KernelKMeansClusteringConfig::getNbAttempts

(

)

const

retrieve number of attempts for K-Means algorithm

Each attempt is associated to a different initialization using K-Means++ algorithm.

getDefaultMaxIteration()

static ipUInt32 ipsdk::math::clustering::KernelKMeansClusteringConfig::getDefaultMaxIteration ( )

inlinestatic

function allowing to retrieve default maximum number of K-Means algorithm iterations for an attempt

setNbMaxIteration()

void ipsdk::math::clustering::KernelKMeansClusteringConfig::setNbMaxIteration

(

const ipUInt32

nbMaxIteration

)

set maximum number of K-Means algorithm iterations for an attempt

Exceptions

ipsdk::math::IPSDKMathException

if nbMaxIteration == 0

getNbMaxIteration()

ipUInt32 ipsdk::math::clustering::KernelKMeansClusteringConfig::getNbMaxIteration

(

)

const

retrieve maximum number of K-Means algorithm iterations for an attempt

setMinChangeRatio()

void ipsdk::math::clustering::KernelKMeansClusteringConfig::setMinChangeRatio

(

const ipReal64

minChangeRatio

)

set minimum ratio for sample assignment change (versus full number of samples) to consider that an iteration has converged

Exceptions

ipsdk::math::IPSDKMathException

if minChangeRatio < 0 || minChangeRatio >= 1

getMinChangeRatio()

ipReal64 ipsdk::math::clustering::KernelKMeansClusteringConfig::getMinChangeRatio

(

)

const

retrieve minimum ratio for sample assignment change (versus full number of samples) to consider that an iteration has converged

setAccuracyThreshold()

void ipsdk::math::clustering::KernelKMeansClusteringConfig::setAccuracyThreshold

(

const ipReal64

accuracyThreshold

)

set accuracy threshold for approximate linear dependence condition

Exceptions

ipsdk::math::IPSDKMathException

if accuracyThreshold < 0

setMaxDictionarySize()

void ipsdk::math::clustering::KernelKMeansClusteringConfig::setMaxDictionarySize

(

const ipUInt32

maxDictionarySize

)

set maximum dictionary size by cluster

Exceptions

ipsdk::math::IPSDKMathException

if maxDictionarySize == 0

Member Data Documentation

_nbAttempts

ipUInt32 ipsdk::math::clustering::KernelKMeansClusteringConfig::_nbAttempts

protected

number of attempts for K-Means algorithm

Each attempt is associated to a different initialization using K-Means++ algorithm.

_nbMaxIteration

ipUInt32 ipsdk::math::clustering::KernelKMeansClusteringConfig::_nbMaxIteration

protected

maximum number of K-Means algorithm iterations for an attempt

_minChangeRatio

ipReal64 ipsdk::math::clustering::KernelKMeansClusteringConfig::_minChangeRatio

protected

minimum ratio for sample assignment change (versus full number of samples) to consider that an iteration has converged

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

• /media/reactivipdev/Nightly/IPSDK_Patch/IPSDK_4_1/IPSDK_Nightly/include/public/IPSDKMath/Clustering/KernelKMeansClusteringConfig.h