In this file we define the enum, constants and utilities functions of the Clustering project. More...

#include <STKernel.h>

Include dependency graph for STK_Clust_Util.h:

This graph shows which files directly or indirectly include this file:

Classes
struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBkQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBkQkD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBkQDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBkQD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBQkD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBQDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjkBQD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBkQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBkQkD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBkQDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBkQD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBQkD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBQDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AkBQD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjBkQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjBkQkD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjBkQDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjBkQD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjBQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_AjBQkD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_ABkQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_ABkQkD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_ABkQDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_ABkQD_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_ABQkDk_ >

struct	STK::hidden::HDCovarianceChooser< Clust::HDCovariance_ABQkD_ >

Namespaces
namespace	STK
	The namespace STK is the main domain space of the Statistical ToolKit project.

namespace	STK::hidden
	The hidden namespace enclose the classes and methods which are used internally by the STK++ classes.

namespace	STK::Clust
	The namespace Clust enclose all the enum and utilities functions needed by the Clustering project.

Enumerations
enum	STK::Clust::initType { STK::Clust::noInit_ = -1 , STK::Clust::randomInit_ = -2 , STK::Clust::randomParamInit_ = 0 , STK::Clust::randomClassInit_ = 1 , STK::Clust::randomFuzzyInit_ = 2 , STK::Clust::valueParamInit_ = 3 }
	initialization type. More...

enum	STK::Clust::algoType { STK::Clust::emAlgo_ = 0 , STK::Clust::cemAlgo_ = 1 , STK::Clust::semAlgo_ = 2 , STK::Clust::semiSemAlgo_ = 3 }
	Estimation algorithms. More...

enum	STK::Clust::algoPredictType { STK::Clust::emPredictAlgo_ , STK::Clust::semiSEMPredictAlgo_ }
	Learning estimation algorithms. More...

enum	STK::Clust::algoLearnType { STK::Clust::imputeAlgo_ , STK::Clust::simulAlgo_ }
	Learning estimation algorithms. More...

enum	STK::Clust::strategyType { STK::Clust::simpleStrategy_ = 0 , STK::Clust::XemStrategy_ = 1 , STK::Clust::SemStrategy_ = 2 , STK::Clust::FullStrategy_ = 3 }
	strategy of estimation More...

enum	STK::Clust::criterionType { STK::Clust::aic_ = 0 , STK::Clust::bic_ = 1 , STK::Clust::icl_ = 2 , STK::Clust::ml_ = 3 }
	type of criterion to use in order to select the mixture model More...

enum	STK::Clust::exceptions { STK::Clust::randomInitFail_ , STK::Clust::randomParamInitFail_ , STK::Clust::randomClassInitFail_ , STK::Clust::randomFuzzyInitFail_ , STK::Clust::estimFail_ , STK::Clust::initializeStepFail_ , STK::Clust::mStepFail_ , STK::Clust::eStepFail_ , STK::Clust::mapStepFail_ , STK::Clust::cStepFail_ , STK::Clust::sStepFail_ }
	Specific exceptions allowing to handle the erroros that can occur in the estimation process. More...

enum	STK::Clust::modelState { STK::Clust::modelCreated_ =0 , STK::Clust::modelInitialized_ =1 , STK::Clust::modelParamInitialized_ =2 , STK::Clust::shortRun_ , STK::Clust::longRun_ , STK::Clust::modelFinalized_ }
	Give the state of the model. More...

enum	STK::Clust::ParsimoniousCovarianceModel { STK::Clust::Covariance_EII_ =100 , STK::Clust::Covariance_VII_ , STK::Clust::Covariance_EEI_ , STK::Clust::Covariance_VEI_ , STK::Clust::Covariance_EVI_ , STK::Clust::Covariance_VVI_ , STK::Clust::Covariance_EEE_ , STK::Clust::Covariance_VEE_ , STK::Clust::Covariance_EVE_ , STK::Clust::Covariance_VVE_ , STK::Clust::Covariance_EEV_ , STK::Clust::Covariance_VEV_ , STK::Clust::Covariance_EVV_ , STK::Clust::Covariance_VVV_ }
	list of the parsimonious covariance models that can be used More...

enum	STK::Clust::HDCovarianceModel { STK::Clust::HDCovariance_AjkBkQkDk_ =120 , STK::Clust::HDCovariance_AjkBkQkD_ , STK::Clust::HDCovariance_AjkBkQDk_ , STK::Clust::HDCovariance_AjkBkQD_ , STK::Clust::HDCovariance_AjkBQkDk_ , STK::Clust::HDCovariance_AjkBQkD_ , STK::Clust::HDCovariance_AjkBQDk_ , STK::Clust::HDCovariance_AjkBQD_ , STK::Clust::HDCovariance_AkBkQkDk_ , STK::Clust::HDCovariance_AkBkQkD_ , STK::Clust::HDCovariance_AkBkQDk_ , STK::Clust::HDCovariance_AkBkQD_ , STK::Clust::HDCovariance_AkBQkDk_ , STK::Clust::HDCovariance_AkBQkD_ , STK::Clust::HDCovariance_AkBQDk_ , STK::Clust::HDCovariance_AkBQD_ , STK::Clust::HDCovariance_AjBkQkDk_ , STK::Clust::HDCovariance_AjBkQkD_ , STK::Clust::HDCovariance_AjBkQDk_ , STK::Clust::HDCovariance_AjBkQD_ , STK::Clust::HDCovariance_AjBQkDk_ , STK::Clust::HDCovariance_AjBQkD_ , STK::Clust::HDCovariance_AjBQDk_ , STK::Clust::HDCovariance_AjBQD_ , STK::Clust::HDCovariance_ABkQkDk_ , STK::Clust::HDCovariance_ABkQkD_ , STK::Clust::HDCovariance_ABkQDk_ , STK::Clust::HDCovariance_ABkQD_ , STK::Clust::HDCovariance_ABQkDk_ , STK::Clust::HDCovariance_ABQkD_ , STK::Clust::HDCovariance_ABQDk_ , STK::Clust::HDCovariance_ABQD_ }
	list of the HD covariance models that can be used More...

enum	STK::Clust::Mixture { STK::Clust::Gamma_ajk_bjk_ =0 , STK::Clust::Gamma_ajk_bk_ , STK::Clust::Gamma_ajk_bj_ , STK::Clust::Gamma_ajk_b_ , STK::Clust::Gamma_ak_bjk_ , STK::Clust::Gamma_ak_bk_ , STK::Clust::Gamma_ak_bj_ , STK::Clust::Gamma_ak_b_ , STK::Clust::Gamma_aj_bjk_ , STK::Clust::Gamma_aj_bk_ , STK::Clust::Gamma_a_bjk_ , STK::Clust::Gamma_a_bk_ , STK::Clust::Gaussian_sjk_ =20 , STK::Clust::Gaussian_sk_ , STK::Clust::Gaussian_sj_ , STK::Clust::Gaussian_s_ , STK::Clust::Gaussian_sjsk_ , STK::Clust::Categorical_pjk_ =40 , STK::Clust::Categorical_pk_ , STK::Clust::Poisson_ljk_ = 60 , STK::Clust::Poisson_lk_ , STK::Clust::Poisson_ljlk_ , STK::Clust::Kmm_sk_ = 80 , STK::Clust::Kmm_s_ , STK::Clust::HDGaussian_AjkBkQkDk_ =120 , STK::Clust::HDGaussian_AjkBkQkD_ , STK::Clust::HDGaussian_AjkBkQDk_ , STK::Clust::HDGaussian_AjkBkQD_ , STK::Clust::HDGaussian_AjkBQkDk_ , STK::Clust::HDGaussian_AjkBQkD_ , STK::Clust::HDGaussian_AjkBQDk_ , STK::Clust::HDGaussian_AjkBQD_ , STK::Clust::HDGaussian_AkBkQkDk_ , STK::Clust::HDGaussian_AkBkQkD_ , STK::Clust::HDGaussian_AkBkQDk_ , STK::Clust::HDGaussian_AkBkQD_ , STK::Clust::HDGaussian_AkBQkDk_ , STK::Clust::HDGaussian_AkBQkD_ , STK::Clust::HDGaussian_AkBQDk_ , STK::Clust::HDGaussian_AkBQD_ , STK::Clust::HDGaussian_AjBkQkDk_ , STK::Clust::HDGaussian_AjBkQkD_ , STK::Clust::HDGaussian_AjBkQDk_ , STK::Clust::HDGaussian_AjBkQD_ , STK::Clust::HDGaussian_AjBQkDk_ , STK::Clust::HDGaussian_AjBQkD_ , STK::Clust::HDGaussian_ABkQkDk_ , STK::Clust::HDGaussian_ABkQkD_ , STK::Clust::HDGaussian_ABkQDk_ , STK::Clust::HDGaussian_ABkQD_ , STK::Clust::HDGaussian_ABQkDk_ , STK::Clust::HDGaussian_ABQkD_ , STK::Clust::HDGaussian_ABQD_ , STK::Clust::unknown_mixture_ = -1 }
	list of the mixtures that can be used by the composer More...

enum	STK::Clust::MixtureClass { STK::Clust::Gamma_ , STK::Clust::DiagGaussian_ , STK::Clust::Categorical_ , STK::Clust::Poisson_ , STK::Clust::Kmm_ , STK::Clust::Matrix_ , STK::Clust::HDGaussian_ , STK::Clust::HDMatrixGaussian_ , STK::Clust::unknown_mixture_class_ = -1 }
	list of the class of mixture implemented in stkpp More...

Functions
initType	STK::Clust::stringToInit (String const &type)
	Convert a String to a initType.

algoType	STK::Clust::stringToAlgo (String const &type)
	Convert a String to an algoType.

algoPredictType	STK::Clust::stringToPredictAlgo (String const &type)
	Convert a String to an algoPredictType.

algoLearnType	STK::Clust::stringToLearnAlgo (String const &type)
	Convert a String to an algoLearnType.

criterionType	STK::Clust::stringToCriterion (String const &type)
	Convert a String to an criterionType.

String	STK::Clust::exceptionToString (exceptions const &type)
	convert a Clust::exceptions to a String.

Mixture	STK::Clust::stringToMixture (String const &type)
	Convert a String to a Mixture.

Mixture	STK::Clust::stringToMixture (String const &type, bool &freeProp)
	convert a string to a Mixture and specify if the model is with free proportions or fixed proportions.

String	STK::Clust::mixtureToString (Mixture const &type)
	convert a Mixture to a String.

String	STK::Clust::mixtureToString (Mixture type, bool freeProp)
	convert a Mixture to a string specifying if the model is with free proportions.

MixtureClass	STK::Clust::mixtureToMixtureClass (Mixture const &type)
	convert a Mixture to a MixtureClass.

IMixtureCriterion *	STK::Clust::createCriterion (Clust::criterionType criterion)

STK::IMixtureCriterion *	STK::Clust::createCriterion (String const &criterion)

IMixtureAlgo *	STK::Clust::createAlgo (Clust::algoType algo, int nbIterMax, Real epsilon)
	utility function for creating an estimation algorithm.

IMixtureAlgoLearn *	STK::Clust::createLearnAlgo (Clust::algoLearnType algo, int nbIterMax, Real epsilon)
	utility function for creating a learning algorithm.

IMixtureAlgoPredict *	STK::Clust::createPredictAlgo (Clust::algoPredictType algo, int nbIterBurn, int nbIterLong, Real epsilon)
	utility function for creating a predicting algorithm.

IMixtureInit *	STK::Clust::createInit (Clust::initType init=defaultInitType, int nbInits=defaultNbInit, Clust::algoType algo=defaultAlgoInInit, int nbIterMax=defaultNbIterMaxInInit, Real epsilon=defaultEpsilonInInit)
	Utility function for creating a model initializer.

IMixtureAlgo *	STK::Clust::createShortRunAlgo (Clust::algoType algo=defaultAlgoShortRun, int nbIterMax=defaultMaxIterShortRun, Real epsilon=defaultEpsilonShortRun)
	utility function for creating a a short Run algorithm.

IMixtureAlgo *	STK::Clust::createLongRunAlgo (Clust::algoType algo=defaultAlgoLongRun, int nbIterMax=defaultMaxIterLongRun, Real epsilon=defaultEpsilonLongRun)
	utility function for creating a long Run algorithm.

IMixtureStrategy *	STK::Clust::createSimpleStrategy (IMixtureComposer &p_composer, int nbTry, IMixtureInit const &p_init, IMixtureAlgo *const &algo)
	Utility function for creating a SimpleStrategy.

IMixtureStrategy *	STK::Clust::createFullStrategy (IMixtureComposer &p_composer, int nbTry, int nbInitRun, IMixtureInit const &p_init, int nbShortRun, IMixtureAlgo const &shortRunAlgo, IMixtureAlgo const &longRunAlgo)
	Utility function for creating a FullStrategy.

Variables
const int	STK::Clust::defaultNbTry = 5
	Default number of try in an estimation strategy.

const Clust::initType	STK::Clust::defaultInitType = randomFuzzyInit_
	Default algorithm type in short run.

const int	STK::Clust::defaultNbInit = 5
	Default number of initializations to perform.

const Clust::algoType	STK::Clust::defaultAlgoInInit = emAlgo_
	Default algorithm type in initialization.

const int	STK::Clust::defaultNbIterMaxInInit = 20
	Default number of iteration in an initialization algorithm.

const Real	STK::Clust::defaultEpsilonInInit = 1e-02
	Default epsilon in the short runs (used in strategy)

const Clust::algoType	STK::Clust::defaultAlgoShortRun = emAlgo_
	Default algorithm type in short run.

const int	STK::Clust::defaultMaxIterShortRun = 200
	Default number of iterations in the short runs (used in FullStrategy)

const Real	STK::Clust::defaultEpsilonShortRun = 1e-04
	Default epsilon in the short runs (used in strategy)

const Clust::algoType	STK::Clust::defaultAlgoLongRun = emAlgo_
	Default algorithm type in long run.

const int	STK::Clust::defaultMaxIterLongRun = 1000
	Default number of iterations in the long run (used in FullStrategy)

const Real	STK::Clust::defaultEpsilonLongRun = 1e-08
	Default epsilon in the long run (used in strategy)

Detailed Description

In this file we define the enum, constants and utilities functions of the Clustering project.

Definition in file STK_Clust_Util.h.

Classes

Namespaces

Enumerations

Functions

Variables

Detailed Description