Clustering using generative models

The project Clustering provides classes for modeling and estimating generative mixture model. More...

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

Classes
struct	STK::hidden::MixtureTraits< Categorical_pjk< Array_ > >
	Traits class for the Categorical_pjk traits policy. More...
class	STK::Categorical_pjk< Array >
	The diagonal Categorical mixture model Categorical_pjk is the most general diagonal Categorical model and has a probability function of the form. More...
struct	STK::hidden::MixtureTraits< Categorical_pk< Array_ > >
	Traits class for the Categorical_pk traits policy. More...
class	STK::Categorical_pk< Array >
	The diagonal Categorical mixture model Categorical_pk is a diagonal Categorical model and has a density function of the form. More...
class	STK::CategoricalBase< Derived >
	Base class for the Categorical models. More...
class	STK::CategoricalBridge< Id, Data >
	template implementation of the IMixtureBridge interface allowing to bridge a STK++ mixture with the composer. More...
class	STK::CategoricalMixtureManager< DataHandler >
	A mixture manager is a factory class for injection dependency in the STK++ derived class of the IMixtureComposer interface class. More...
struct	STK::ModelParameters< Clust::Categorical_pjk_ >
	Structure encapsulating the parameters of a Categorical_pjk model. More...
struct	STK::ModelParameters< Clust::Categorical_pk_ >
	Structure encapsulating the parameters of a Categorical_pk model. More...
class	STK::DiagGaussian_s< Array >
	The diagonal DiagGaussian_s mixture model hse a density function of the form. More...
class	STK::DiagGaussian_sj< Array >
	The diagonal Gaussian mixture model DiagGaussian_sj have a density function of the form. More...
struct	STK::hidden::MixtureTraits< DiagGaussian_sjk< Array_ > >
	Traits class for the DiagGaussian_sjk traits policy. More...
class	STK::DiagGaussian_sjk< Array >
	The diagonal Gaussian mixture model DiagGaussian_sjk is the most general diagonal Gaussian model and have a density function of the form. More...
struct	STK::hidden::MixtureTraits< DiagGaussian_sjsk< Array_ > >
	Traits class for the DiagGaussian_sjsk traits policy. More...
class	STK::DiagGaussian_sjsk< Array >
	The diagonal Gaussian mixture model DiagGaussian_sjsk is an intermediate diagonal Gaussian model with density function of the form. More...
struct	STK::hidden::MixtureTraits< DiagGaussian_sk< Array_ > >
	Traits class for the DiagGaussian_sk traits policy. More...
class	STK::DiagGaussian_sk< Array >
	The diagonal Gaussian mixture model DiagGaussian_sk assumes an equal standard deviation in each cluster and has a density function of the form. More...
class	STK::DiagGaussianBase< Derived >
	Base class for the diagonal Gaussian models. More...
class	STK::DiagGaussianBridge< Id, Data >
	template implementation of the IMixture interface allowing to bridge a STK++ mixture with the composer. More...
class	STK::DiagGaussianMixtureManager< DataHandler >
	A mixture manager is a factory class for injection dependency in the STK++ derived class of the IMixtureComposer class. More...
struct	STK::ModelParameters< Clust::Gaussian_sjk_ >
	Structure encapsulating the parameters of a STK::DiagGaussian_sjk model. More...
struct	STK::ModelParameters< Clust::Gaussian_sk_ >
	Structure encapsulating the parameters of a STK::DiagGaussian_sk model. More...
struct	STK::ModelParameters< Clust::Gaussian_sj_ >
	Structure encapsulating the parameters of a STK::DiagGaussian_sj model. More...
struct	STK::ModelParameters< Clust::Gaussian_s_ >
	Structure encapsulating the parameters of a STK::DiagGaussian_s model. More...
struct	STK::ModelParameters< Clust::Gaussian_sjsk_ >
	Structure encapsulating the parameters of a Gaussian_sjsk mixture model. More...
struct	STK::hidden::MixtureTraits< Gamma_a_bjk< Array_ > >
	Traits class for the Gamma_a_bjk traits policy. More...
class	STK::Gamma_a_bjk< Array >
	Gamma_a_bjk is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_a_bk< Array_ > >
	Traits class for the Gamma_a_bk traits policy. More...
class	STK::Gamma_a_bk< Array >
	Gamma_a_bk is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_aj_bjk< Array_ > >
	Traits class for the Gamma_aj_bjk traits policy. More...
class	STK::Gamma_aj_bjk< Array >
	Gamma_aj_bjk is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_aj_bk< Array_ > >
	Traits class for the Gamma_aj_bk traits policy. More...
class	STK::Gamma_aj_bk< Array >
	Gamma_aj_bk is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ajk_b< Array_ > >
	Traits class for the Gamma_ajk_b traits policy. More...
class	STK::Gamma_ajk_b< Array >
	Gamma_ajk_b is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ajk_bj< Array_ > >
	Traits class for the Gamma_ajk_bj traits policy. More...
class	STK::Gamma_ajk_bj< Array >
	Gamma_ajk_bj is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ajk_bjk< Array_ > >
	Traits class for the Gamma_ajk_bjk traits policy. More...
class	STK::Gamma_ajk_bjk< Array >
	Gamma_ajk_bjk is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ajk_bk< Array_ > >
	Traits class for the Gamma_ajk_bk traits policy. More...
class	STK::Gamma_ajk_bk< Array >
	Gamma_ajk_bk is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ak_b< Array_ > >
	Traits class for the Gamma_ak_b traits policy. More...
class	STK::Gamma_ak_b< Array >
	Gamma_ak_b is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ak_bj< Array_ > >
	Traits class for the Gamma_ak_bj traits policy. More...
class	STK::Gamma_ak_bj< Array >
	Gamma_ak_bj is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ak_bjk< Array_ > >
	Traits class for the Gamma_ak_bjk traits policy. More...
class	STK::Gamma_ak_bjk< Array >
	Gamma_ak_bjk is a mixture model of the following form. More...
struct	STK::hidden::MixtureTraits< Gamma_ak_bk< Array_ > >
	Traits class for the Gamma_ak_bk traits policy. More...
class	STK::Gamma_ak_bk< Array >
	Gamma_ak_bk is a mixture model of the following form. More...
class	STK::GammaBase< Derived >
	Base class for the gamma models. More...
class	STK::GammaBridge< Id, Data >
	template implementation of the IMixtureBridge interface allowing to bridge a STK++ mixture with the composer. More...
class	STK::GammaMixtureManager< DataHandler >
	A mixture manager is a factory class for injection dependency in the STK++ derived class of the MixtureComposer class. More...
struct	STK::ModelParameters< Clust::Gamma_a_bjk_ >
	Structure encapsulating the parameters of a Gamma_a_bjk_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_a_bk_ >
	Structure encapsulating the parameters of a Gamma_a_bk_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_aj_bjk_ >
	Structure encapsulating the parameters of a Gamma_aj_bjk_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_aj_bk_ >
	Structure encapsulating the parameters of a Gamma_aj_bk_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ajk_b_ >
	Structure encapsulating the parameters of a Gamma_ajk_b_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ajk_bj_ >
	Structure encapsulating the parameters of a Gamma_ajk_bj_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ajk_bjk_ >
	Structure encapsulating the parameters of a Gamma_ajk_bjk_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ajk_bk_ >
	Structure encapsulating the parameters of a Gamma_ajk_bk_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ak_b_ >
	Structure encapsulating the parameters of a Gamma_ak_b_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ak_bj_ >
	Structure encapsulating the parameters of a Gamma_ak_bj_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ak_bjk_ >
	Structure encapsulating the parameters of a Gamma_ak_bjk_ mixture model. More...
struct	STK::ModelParameters< Clust::Gamma_ak_bk_ >
	Structure encapsulating the parameters of a Gamma_ak_bk_ mixture model. More...
class	STK::HDMatrixGaussianBridge< IdRow, IdCol, Data >
	template implementation of the IMixture interface allowing to bridge a STK++ mixture with the composer. More...
struct	STK::hidden::MixtureTraits< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >
	Traits class for the HDMatrixGaussianModel traits policy. More...
class	STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >
	Main class for HD matrix valued matrix models. More...
struct	STK::HDMatrixModelParameters< Array_ >
	structure storing the parameters of the HD matrix valued mixture More...
struct	STK::hidden::MixtureTraits< HDGaussian_AjkBkQkD_< Array_ > >
	Traits class for the MixtureHDGaussian_ajk_bk_qk_d traits policy. More...
struct	STK::ModelParameters< Clust::HDGaussian_AjkBkQkD_ >
	Structure encapsulating the parameters of a MixturGaussian_sj model. More...
class	STK::HDGaussian_AjkBkQkD< Array >
	The diagonal Gaussian mixture model HDGaussian_AjkBkQkD is the most general HD Gaussian model and have a density function of the form. More...
class	STK::HDGaussianBase< Derived >
	Base class for the diagonal Gaussian models. More...
class	STK::HDGaussianBridge< Id, Data >
	template implementation of the IMixture interface allowing to bridge a STK++ mixture with the composer. More...
class	STK::KernelMixtureManager
	A mixture manager is a factory class for injection dependency in the STK++ derived class of the MixtureComposer class. More...
struct	STK::ModelParameters< Clust::Kmm_s_ >
	Structure encapsulating the parameters of a Kmm_s model. More...
struct	STK::ModelParameters< Clust::Kmm_sk_ >
	Structure encapsulating the parameters of a Kmm_sk model. More...
struct	STK::hidden::MixtureTraits< Kmm_s >
	MixtureTraits class for the Kmm_s traits policy. More...
class	STK::Kmm_s
	The Gaussian mixture model Kmm_s is an isotrope Gaussian mixture model on a kernel space. More...
struct	STK::hidden::MixtureTraits< Kmm_sk >
	Traits class for the Kmm_sk traits policy. More...
class	STK::Kmm_sk
	The Gaussian mixture model Kmm_sk is an isotrope Gaussian mixture model on a kernel space. More...
class	STK::KmmBase< Derived >
	Base class for the Gaussian Kernel Mixture Models. More...
class	STK::KmmBridge< Id, Data >
	template implementation of the IMixture interface allowing to bridge a STK++ kernel mixture with the composer. More...
class	STK::IMixtureAlgo
	Interface base class for the algorithms. More...
class	STK::IMixtureAlgoLearn
	Interface base class for the learning algorithms. More...
class	STK::IMixtureAlgoPredict
	Interface base class for predicting algorithms. More...
class	STK::EMAlgo
	Implementation of the EM algorithm. More...
class	STK::CEMAlgo
	Implementation of the SEM algorithm. More...
class	STK::SEMAlgo
	Implementation of the SEM algorithm. More...
class	STK::SemiSEMAlgo
	Implementation of the SemiSEM algorithm. More...
class	STK::ImputeAlgo
	Implementation of the ImputeAlgo learning algorithm. More...
class	STK::SimulAlgo
	Implementation of the SimulAlgo learning algorithm. More...
class	STK::EMPredict
	Implementation of the EMPredict algorithm. More...
class	STK::SemiSEMPredict
	Implementation of the SemiSEMPredict algorithm. More...
class	STK::IMixtureCriterion
	Interface base class for the selection model criterion. More...
class	STK::AICMixtureCriterion
	Derived class of Criterion for computing the AIC Criterion The AIC criteria of a given model M is a penalization of the likelihood given by the formula. More...
class	STK::BICMixtureCriterion
	Derived class of Criterion for computing the BIC Criterion The Bic criteria of a model M is a penalization of the likelihood given by the formula. More...
class	STK::ICLMixtureCriterion
	Derived class of IMixtureCriterion for computing the ICL Criterion The ICL criteria of a model M is a penalization of the likelihood given by the formula. More...
class	STK::MLMixtureCriterion
	Derived class of Criterion for computing the Maximum Likelihood Criterion This criterion does not penalize the model and return minux two times the log likelihood of the model. More...
class	STK::IMixtureInit
	Interface base class for the initializations. More...
class	STK::RandomInit
	Implementation of the random initialization. More...
class	STK::ClassInit
	Initialization by simulating a realization of the class labels zi accordingly to the initial proportions. More...
class	STK::FuzzyInit
	Initialization by simulating the tik accordingly to the initial proportions. More...
struct	STK::FullStrategyParam
	helper structure encapsulating the parameters of the Full strategy More...
class	STK::FullStrategy
	A FullStrategy is based on the following paradigm: More...
class	STK::IMixtureStrategy
	Interface base class for all the strategies. More...
struct	STK::SimpleStrategyParam
	helper structure encapsulating the parameters of the simple strategy More...
class	STK::SimpleStrategy
	A SimpleStrategy is just nbTry long run. More...
struct	STK::XemStrategyParam
	helper structure encapsulating the parameters of the Xem strategy More...
class	STK::XemStrategy
	A XemStrategy is based on the following paradigm: More...
struct	STK::hidden::MixtureTraits< Poisson_ljk< Array_ > >
	Traits class for the Poisson_ljk traits policy. More...
class	STK::Poisson_ljk< Array >
	The Poisson mixture model Poisson_ljk is the most general Poisson model and have a probability function of the form. More...
struct	STK::hidden::MixtureTraits< Poisson_ljlk< Array_ > >
	Traits class for the Poisson_ljlk traits policy. More...
class	STK::Poisson_ljlk< Array >
	The Poisson mixture model Poisson_ljlk is a Poisson model with a probability function of the form. More...
struct	STK::hidden::MixtureTraits< Poisson_lk< Array_ > >
	Traits class for the Poisson_lk traits policy. More...
class	STK::Poisson_lk< Array >
	The Poisson mixture model Poisson_lk has a probability function of the form. More...
class	STK::PoissonBase< Derived >
	Base class for the Poisson models. More...
class	STK::PoissonBridge< Id, Data >
	template implementation of the IMixtureBridge interface allowing to bridge a STK++ Poisson mixture with the composer. More...
class	STK::PoissonMixtureManager< DataHandler >
	A mixture manager is a factory class for injection dependency in the STK++ derived class of the MixtureComposer class. More...
struct	STK::ModelParameters< Clust::Poisson_ljlk_ >
	Structure encapsulating the parameters of a Poisson_ljlk model. More...
struct	STK::ModelParameters< Clust::Poisson_ljk_ >
	Structure encapsulating the parameters of a Poisson_ljlk model. More...
struct	STK::ModelParameters< Clust::Poisson_lk_ >
	Structure encapsulating the parameters of a Poisson_lk model. More...
struct	STK::ModelParameters< Id >
	struct storing the parameters of the mixture. More...
class	STK::IMixture
	Interface base class for all the mixture models that will be processed by the composer. More...
class	STK::IMixtureBridge< Derived >
	Interface base class for the bridges of the STK++ mixture. More...
class	STK::IMixtureComposer
	Base class for Mixture (composed) model. More...
class	STK::IMixtureDensity< Derived >
	Base class for all Mixture densities. More...
class	STK::IMixtureLearner
	Base class for Learner of a Mixture mixed model. More...
class	STK::IMixtureManager< Derived >
	Interface base class for mixture managers. More...
class	STK::IMixtureModel< Derived >
	Main interface class for mixture models. More...
class	STK::IMixtureModelBase
	Base class for all Mixture model. More...
class	STK::MixtureComposer
	Main class for handling composed mixture models. More...
class	STK::StrategyFacade
	facade design pattern. More...
class	STK::LearnFacade
	facade design pattern. More...
class	STK::MixtureLearner
	Main class for learning mixture models. More...
class	STK::MixtureSemiLearner
	Base class for Learning a Mixture mixed model when some classes are known. More...
class	STK::DataBridge< Data >
	bridge a data set in order to handle its missing values. More...

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)
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

The project Clustering provides classes for modeling and estimating generative mixture model.

The aim of this project is to define Interfaces and specialized Classes in order to manipulate and estimate the parameters of any kind of generative mixture model.

In statistics, a mixture model is a probabilistic model for representing the presence of sub-populations within an overall population, without requiring that an observed data-set should identify the sub-population to which an individual observation belongs. Formally a mixture model </ corresponds to the mixture distribution that represents the probability distribution of observations in the overall population. However, while problems associated with mixture distributions relate to deriving the properties of the overall population from those of the sub-populations, mixture models are used to make statistical inferences about the properties of the sub-populations given only observations on the pooled population, without sub-population-identity information.

Some ways of implementing mixture models involve steps that attribute postulated sub-population-identities to individual observations (or weights towards such sub-populations), in which case these can be regarded as types of unsupervised learning or clustering procedures. However not all inference procedures involve such steps.

Enumeration Type Documentation

algoLearnType

enum STK::Clust::algoLearnType

Learning estimation algorithms.

Enumerator
imputeAlgo_
simulAlgo_

Definition at line 193 of file STK_Clust_Util.h.

{
  imputeAlgo_,
  simulAlgo_
};

algoPredictType

enum STK::Clust::algoPredictType

Learning estimation algorithms.

Enumerator
emPredictAlgo_
semiSEMPredictAlgo_

Definition at line 170 of file STK_Clust_Util.h.

{
  emPredictAlgo_,
  semiSEMPredictAlgo_
};

algoType

enum STK::Clust::algoType

Estimation algorithms.

Enumerator
emAlgo_
cemAlgo_
semAlgo_
semiSemAlgo_

Definition at line 138 of file STK_Clust_Util.h.

{
  emAlgo_ = 0,
  cemAlgo_ = 1,
  semAlgo_ = 2,
  semiSemAlgo_ = 3
};

criterionType

enum STK::Clust::criterionType

type of criterion to use in order to select the mixture model

Enumerator
aic_
bic_
icl_
ml_

Definition at line 229 of file STK_Clust_Util.h.

{
  aic_  = 0,
  bic_  = 1,
  icl_  = 2,
  ml_   = 3
};

exceptions

enum STK::Clust::exceptions

Specific exceptions allowing to handle the erroros that can occur in the estimation process.

Enumerator
randomInitFail_
randomParamInitFail_
randomClassInitFail_
randomFuzzyInitFail_
estimFail_
initializeStepFail_
mStepFail_
eStepFail_
mapStepFail_
cStepFail_
sStepFail_

Definition at line 257 of file STK_Clust_Util.h.

{
  randomInitFail_,
  randomParamInitFail_,
  randomClassInitFail_,
  randomFuzzyInitFail_,
  estimFail_,
  initializeStepFail_,
  mStepFail_,
  eStepFail_,
  mapStepFail_,
  cStepFail_,
  sStepFail_
};

HDCovarianceModel

enum STK::Clust::HDCovarianceModel

list of the HD covariance models that can be used

Enumerator
HDCovariance_AjkBkQkDk_
HDCovariance_AjkBkQkD_
HDCovariance_AjkBkQDk_
HDCovariance_AjkBkQD_
HDCovariance_AjkBQkDk_
HDCovariance_AjkBQkD_
HDCovariance_AjkBQDk_
HDCovariance_AjkBQD_
HDCovariance_AkBkQkDk_
HDCovariance_AkBkQkD_
HDCovariance_AkBkQDk_
HDCovariance_AkBkQD_
HDCovariance_AkBQkDk_
HDCovariance_AkBQkD_
HDCovariance_AkBQDk_
HDCovariance_AkBQD_
HDCovariance_AjBkQkDk_
HDCovariance_AjBkQkD_
HDCovariance_AjBkQDk_
HDCovariance_AjBkQD_
HDCovariance_AjBQkDk_
HDCovariance_AjBQkD_
HDCovariance_AjBQDk_
HDCovariance_AjBQD_
HDCovariance_ABkQkDk_
HDCovariance_ABkQkD_
HDCovariance_ABkQDk_
HDCovariance_ABkQD_
HDCovariance_ABQkDk_
HDCovariance_ABQkD_
HDCovariance_ABQDk_
HDCovariance_ABQD_

Definition at line 315 of file STK_Clust_Util.h.

{
  HDCovariance_AjkBkQkDk_ =120,
  HDCovariance_AjkBkQkD_,
  HDCovariance_AjkBkQDk_,
  HDCovariance_AjkBkQD_,
  HDCovariance_AjkBQkDk_,
  HDCovariance_AjkBQkD_,
  HDCovariance_AjkBQDk_,
  HDCovariance_AjkBQD_,
  HDCovariance_AkBkQkDk_,
  HDCovariance_AkBkQkD_,
  HDCovariance_AkBkQDk_,
  HDCovariance_AkBkQD_,
  HDCovariance_AkBQkDk_,
  HDCovariance_AkBQkD_,
  HDCovariance_AkBQDk_,
  HDCovariance_AkBQD_,
  HDCovariance_AjBkQkDk_,
  HDCovariance_AjBkQkD_,
  HDCovariance_AjBkQDk_,
  HDCovariance_AjBkQD_,
  HDCovariance_AjBQkDk_,
  HDCovariance_AjBQkD_,
  HDCovariance_AjBQDk_,
  HDCovariance_AjBQD_,
  HDCovariance_ABkQkDk_,
  HDCovariance_ABkQkD_,
  HDCovariance_ABkQDk_,
  HDCovariance_ABkQD_,
  HDCovariance_ABQkDk_,
  HDCovariance_ABQkD_,
  HDCovariance_ABQDk_,
  HDCovariance_ABQD_ // =151
};

initType

enum STK::Clust::initType

initialization type.

There is four ways to initialize the mixture model:

• using random values for the parameters
• using random class for the sampling
• using random probabilities class for the sampling
• using parameters values

Enumerator
noInit_	no initialization
randomInit_	DEPRECATED.
randomParamInit_	initialize randomly the parameters
randomClassInit_	initialize randomly the class labels
randomFuzzyInit_	initialize randomly the partnership class probabilities
valueParamInit_	initialize parameters using given values

Definition at line 106 of file STK_Clust_Util.h.

{
  noInit_ = -1,         
  randomInit_ = -2,     
  randomParamInit_ = 0, 
  randomClassInit_ = 1, 
  randomFuzzyInit_ = 2, 
  valueParamInit_ = 3   
};

Mixture

enum STK::Clust::Mixture

list of the mixtures that can be used by the composer

Enumerator
Gamma_ajk_bjk_
Gamma_ajk_bk_
Gamma_ajk_bj_
Gamma_ajk_b_
Gamma_ak_bjk_
Gamma_ak_bk_
Gamma_ak_bj_
Gamma_ak_b_
Gamma_aj_bjk_
Gamma_aj_bk_
Gamma_a_bjk_
Gamma_a_bk_
Gaussian_sjk_
Gaussian_sk_
Gaussian_sj_
Gaussian_s_
Gaussian_sjsk_
Categorical_pjk_
Categorical_pk_
Poisson_ljk_
Poisson_lk_
Poisson_ljlk_
Kmm_sk_
Kmm_s_
HDGaussian_AjkBkQkDk_
HDGaussian_AjkBkQkD_
HDGaussian_AjkBkQDk_
HDGaussian_AjkBkQD_
HDGaussian_AjkBQkDk_
HDGaussian_AjkBQkD_
HDGaussian_AjkBQDk_
HDGaussian_AjkBQD_
HDGaussian_AkBkQkDk_
HDGaussian_AkBkQkD_
HDGaussian_AkBkQDk_
HDGaussian_AkBkQD_
HDGaussian_AkBQkDk_
HDGaussian_AkBQkD_
HDGaussian_AkBQDk_
HDGaussian_AkBQD_
HDGaussian_AjBkQkDk_
HDGaussian_AjBkQkD_
HDGaussian_AjBkQDk_
HDGaussian_AjBkQD_
HDGaussian_AjBQkDk_
HDGaussian_AjBQkD_
HDGaussian_ABkQkDk_
HDGaussian_ABkQkD_
HDGaussian_ABkQDk_
HDGaussian_ABkQD_
HDGaussian_ABQkDk_
HDGaussian_ABQkD_
HDGaussian_ABQD_
unknown_mixture_

Definition at line 617 of file STK_Clust_Util.h.

{
  Gamma_ajk_bjk_ =0,
  Gamma_ajk_bk_,
  Gamma_ajk_bj_,
  Gamma_ajk_b_,
  Gamma_ak_bjk_,
  Gamma_ak_bk_,
  Gamma_ak_bj_,
  Gamma_ak_b_,
  Gamma_aj_bjk_,
  Gamma_aj_bk_,
  Gamma_a_bjk_,
  Gamma_a_bk_, // = 11
  Gaussian_sjk_ =20,
  Gaussian_sk_,
  Gaussian_sj_,
  Gaussian_s_,
  Gaussian_sjsk_, // = 24
  Categorical_pjk_ =40,
  Categorical_pk_,
  Poisson_ljk_ = 60,
  Poisson_lk_,
  Poisson_ljlk_,
  Kmm_sk_ = 80,
  Kmm_s_,
  HDGaussian_AjkBkQkDk_ =120,
  HDGaussian_AjkBkQkD_,
  HDGaussian_AjkBkQDk_,
  HDGaussian_AjkBkQD_,
  HDGaussian_AjkBQkDk_,
  HDGaussian_AjkBQkD_,
  HDGaussian_AjkBQDk_,
  HDGaussian_AjkBQD_,
  HDGaussian_AkBkQkDk_,
  HDGaussian_AkBkQkD_,
  HDGaussian_AkBkQDk_,
  HDGaussian_AkBkQD_,
  HDGaussian_AkBQkDk_,
  HDGaussian_AkBQkD_,
  HDGaussian_AkBQDk_,
  HDGaussian_AkBQD_,
  HDGaussian_AjBkQkDk_,
  HDGaussian_AjBkQkD_,
  HDGaussian_AjBkQDk_,
  HDGaussian_AjBkQD_,
  HDGaussian_AjBQkDk_,
  HDGaussian_AjBQkD_,
  HDGaussian_ABkQkDk_,
  HDGaussian_ABkQkD_,
  HDGaussian_ABkQDk_,
  HDGaussian_ABkQD_,
  HDGaussian_ABQkDk_,
  HDGaussian_ABQkD_,
  HDGaussian_ABQD_,   // =148
  unknown_mixture_ = -1
};

MixtureClass

enum STK::Clust::MixtureClass

list of the class of mixture implemented in stkpp

Enumerator
Gamma_
DiagGaussian_
Categorical_
Poisson_
Kmm_
Matrix_
HDGaussian_
HDMatrixGaussian_
unknown_mixture_class_

Definition at line 678 of file STK_Clust_Util.h.

{
  Gamma_,
  DiagGaussian_,
  Categorical_,
  Poisson_,
  Kmm_,
  Matrix_,
  HDGaussian_,
  HDMatrixGaussian_,
  unknown_mixture_class_ = -1
};

modelState

enum STK::Clust::modelState

Give the state of the model.

Enumerator
modelCreated_	the model has been created but is not initialized
modelInitialized_	the model is initialized and its parameters are initialized to default values
modelParamInitialized_	The parameters of the model have been initialized.
shortRun_	A short run has been done.
longRun_	A long run has been done.
modelFinalized_	the model is finalized

Definition at line 282 of file STK_Clust_Util.h.

{
  modelCreated_ =0,         
  modelInitialized_ =1,     
  modelParamInitialized_=2, 
  shortRun_,                
  longRun_,                 
  modelFinalized_           
};

ParsimoniousCovarianceModel

enum STK::Clust::ParsimoniousCovarianceModel

list of the parsimonious covariance models that can be used

Enumerator
Covariance_EII_
Covariance_VII_
Covariance_EEI_
Covariance_VEI_
Covariance_EVI_
Covariance_VVI_
Covariance_EEE_
Covariance_VEE_
Covariance_EVE_
Covariance_VVE_
Covariance_EEV_
Covariance_VEV_
Covariance_EVV_
Covariance_VVV_

Definition at line 295 of file STK_Clust_Util.h.

{
  Covariance_EII_ =100,
  Covariance_VII_,
  Covariance_EEI_,
  Covariance_VEI_,
  Covariance_EVI_,
  Covariance_VVI_,
  Covariance_EEE_,
  Covariance_VEE_,
  Covariance_EVE_,
  Covariance_VVE_,
  Covariance_EEV_,
  Covariance_VEV_,
  Covariance_EVV_,
  Covariance_VVV_  // =114
};

strategyType

enum STK::Clust::strategyType

strategy of estimation

Enumerator
simpleStrategy_
XemStrategy_
SemStrategy_
FullStrategy_

Definition at line 218 of file STK_Clust_Util.h.

{
  simpleStrategy_ = 0,
  XemStrategy_    = 1, // not implemented
  SemStrategy_    = 2,
  FullStrategy_   = 3
};

Function Documentation

createAlgo()

IMixtureAlgo * STK::Clust::createAlgo	(	Clust::algoType	algo,
		int	nbIterMax,
		Real	epsilon
	)

utility function for creating an estimation algorithm.

Parameters

algo	the algorithm to create
nbIterMax,epsilon	the maximal number of iteration and the tolerance of the algorithm

Definition at line 670 of file STK_Clust_Util.cpp.

{
  IMixtureAlgo* p_algo = 0;
  switch (algo)
  {
  case emAlgo_:
    p_algo = new EMAlgo();
    break;
  case cemAlgo_:
    p_algo = new CEMAlgo();
    break;
  case semAlgo_:
    p_algo = new SEMAlgo();
    break;
  case semiSemAlgo_:
    p_algo = new SemiSEMAlgo();
    break;
  default:
    break;
  }
  if (p_algo)
  {
    p_algo->setNbIterMax(nbIterMax);
    p_algo->setEpsilon(epsilon);
  }
  return p_algo;
}

References STK::Clust::cemAlgo_, STK::Clust::emAlgo_, STK::Clust::semAlgo_, and STK::Clust::semiSemAlgo_.

Referenced by STK::StrategyFacade::createFullStrategy(), STK::Clust::createInit(), STK::Clust::createLongRunAlgo(), STK::Clust::createShortRunAlgo(), and STK::StrategyFacade::createSimpleStrategy().

createCriterion()

IMixtureCriterion * STK::Clust::createCriterion

(

Clust::criterionType

criterion

)

Parameters

criterion

selection criterion to use

Returns

a pointer on the class computing the criterion

Definition at line 637 of file STK_Clust_Util.cpp.

{
  IMixtureCriterion* p_criter = 0;
  switch (type)
  {
  case aic_:
    p_criter = new AICMixtureCriterion();
    break;
  case bic_:
    p_criter = new BICMixtureCriterion();
    break;
  case icl_:
    p_criter = new ICLMixtureCriterion();
    break;
  case ml_:
    p_criter = new MLMixtureCriterion();
    break;
  }
  return p_criter;
}

References STK::Clust::aic_, STK::Clust::bic_, STK::Clust::icl_, and STK::Clust::ml_.

Referenced by STK::Clust::createCriterion().

createFullStrategy()

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.

Parameters

p_composer	the composer to which we want to apply a the strategy.
nbTry	the maximal number of tries.
nbInitRun	the number of initialization to perform.
p_init	the initializer to use.
nbShortRun	the number of shortRun.
shortRunAlgo	the algorithm to use in the short run.
longRunAlgo	the algorithm to use in the long run.

Returns

an instance of the FullStrategy

Definition at line 821 of file STK_Clust_Util.cpp.

{
  FullStrategyParam* p_strategyParam = new FullStrategyParam();
  p_strategyParam->nbInitRun_  = nbInitRun;
  p_strategyParam->nbShortRun_  = nbShortRun;
  p_strategyParam->p_shortAlgo_ = shortRunAlgo;
  p_strategyParam->p_longAlgo_  = longRunAlgo;
  FullStrategy* p_strategy = new FullStrategy(p_composer);
  p_strategy->setNbTry(nbTry);
  p_strategy->setMixtureInit(p_init);
  p_strategy->setParam(p_strategyParam);
  return p_strategy;
}

Referenced by STK::StrategyFacade::createFullStrategy().

createInit()

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.

Parameters

init	the kind of initializer to create
nbInits	the number of initialization to try
algo	the kind of algorithm to add to the initializer
nbIterMax,epsilon	the maximal number of iteration and the tolerance of the initialization algorithm

Definition at line 759 of file STK_Clust_Util.cpp.

{
  IMixtureInit* p_init = 0;
  switch (init)
  {
    case Clust::noInit_:
      p_init = 0;
      break;
    case Clust::randomInit_:
      p_init = new RandomInit();
      break;
    case Clust::randomParamInit_:
      p_init = new RandomInit();
      break;
    case Clust::randomClassInit_:
      p_init = new ClassInit();
      break;
    case Clust::randomFuzzyInit_:
      p_init = new FuzzyInit();
      break;
    default:
      break;
  }
  if (p_init)
  {
    p_init->setNbTry(nbInits);
    p_init->setInitAlgo(Clust::createAlgo(algo, nbIterMax, epsilon));
  }
  return p_init;
}

References STK::Clust::createAlgo(), STK::Clust::noInit_, STK::Clust::randomClassInit_, STK::Clust::randomFuzzyInit_, STK::Clust::randomInit_, and STK::Clust::randomParamInit_.

Referenced by STK::StrategyFacade::createFullStrategy(), and STK::StrategyFacade::createSimpleStrategy().

createLearnAlgo()

IMixtureAlgoLearn * STK::Clust::createLearnAlgo	(	Clust::algoLearnType	algo,
		int	nbIterMax,
		Real	epsilon
	)

utility function for creating a learning algorithm.

Parameters

algo	the algorithm to create
nbIterMax,epsilon	the maximal number of iteration and the tolerance of the algorithm

Definition at line 703 of file STK_Clust_Util.cpp.

{
  IMixtureAlgoLearn* p_algo = 0;
  switch (algo)
  {
  case imputeAlgo_:
    p_algo = new ImputeAlgo();
    break;
  case simulAlgo_:
    p_algo = new SimulAlgo();
    break;
  default:
    break;
  }
  if (p_algo)
  {
    p_algo->setNbIterMax(nbIterMax);
    p_algo->setEpsilon(epsilon);
  }
  return p_algo;
}

References STK::Clust::imputeAlgo_, and STK::Clust::simulAlgo_.

Referenced by STK::LearnFacade::createImputeAlgo(), and STK::LearnFacade::createSimulAlgo().

createLongRunAlgo()

IMixtureAlgo * STK::Clust::createLongRunAlgo ( Clust::algoType  algo = defaultAlgoLongRun, int  nbIterMax = defaultMaxIterLongRun, Real  epsilon = defaultEpsilonLongRun  )

inline

utility function for creating a long Run algorithm.

Parameters

algo	the algorithm to create
nbIterMax	the maximal number of iteration of the algorithm
epsilon	the tolerance of the algorithm

Definition at line 946 of file STK_Clust_Util.h.

{ return createAlgo(algo, nbIterMax, epsilon);}

References STK::Clust::createAlgo().

createPredictAlgo()

IMixtureAlgoPredict * STK::Clust::createPredictAlgo	(	Clust::algoPredictType	algo,
		int	nbIterBurn,
		int	nbIterLong,
		Real	epsilon
	)

utility function for creating a predicting algorithm.

Parameters

algo	the algorithm to create
nbIterBurn,nbIterLong,epsilon	number of iteration of the burning and estimation steps and tolerance of the algorithm

Definition at line 730 of file STK_Clust_Util.cpp.

{
  IMixtureAlgoPredict* p_algo = 0;
  switch (algo)
  {
    case emPredictAlgo_:
      p_algo = new EMPredict();
      break;
    case semiSEMPredictAlgo_:
      p_algo = new SemiSEMPredict();
      break;
    default:
      break;
  }
  if (p_algo)
  {
    p_algo->setNbIterBurn(nbIterBurn);
    p_algo->setNbIterLong(nbIterLong);
    p_algo->setEpsilon(epsilon);
  }
  return p_algo;
}

References STK::Clust::emPredictAlgo_, and STK::Clust::semiSEMPredictAlgo_.

createShortRunAlgo()

IMixtureAlgo * STK::Clust::createShortRunAlgo ( Clust::algoType  algo = defaultAlgoShortRun, int  nbIterMax = defaultMaxIterShortRun, Real  epsilon = defaultEpsilonShortRun  )

inline

utility function for creating a a short Run algorithm.

Parameters

algo	the algorithm to create
nbIterMax	the maximal number of iteration of the algorithm
epsilon	the tolerance of the algorithm

Definition at line 936 of file STK_Clust_Util.h.

{ return createAlgo(algo, nbIterMax, epsilon);}

References STK::Clust::createAlgo().

createSimpleStrategy()

IMixtureStrategy * STK::Clust::createSimpleStrategy	(	IMixtureComposer *&	p_composer,
		int	nbTry,
		IMixtureInit *const &	p_init,
		IMixtureAlgo *const &	algo
	)

Utility function for creating a SimpleStrategy.

Parameters

p_composer	the composer to which we want to apply a the strategy.
nbTry	the number of tries.
p_init	the initializer to use.
algo	the algorithm to use in the long run.

Returns

an instance of the SimpleStrategy

Definition at line 797 of file STK_Clust_Util.cpp.

{
  SimpleStrategyParam* p_strategyParam = new SimpleStrategyParam();
  p_strategyParam->p_algo_ = algo;
  SimpleStrategy* p_strategy = new SimpleStrategy(p_composer);
  p_strategy->setNbTry(nbTry);
  p_strategy->setMixtureInit(p_init);
  p_strategy->setParam(p_strategyParam);
  return p_strategy;
}

Referenced by STK::StrategyFacade::createSimpleStrategy().

exceptionToString()

String STK::Clust::exceptionToString

(

exceptions const &

type

)

convert a Clust::exceptions to a String.

Parameters

type	the type of exception that occur

Returns

the string associated to this exception.

Definition at line 178 of file STK_Clust_Util.cpp.

{
  if (type == randomInitFail_)      return String(_T("RandomInit fail"));
  if (type == randomClassInitFail_) return String(_T("RandomClassInit fail"));
  if (type == randomFuzzyInitFail_) return String(_T("RandomFuzzyInit fail"));
  if (type == randomParamInitFail_) return String(_T("RandomParamInit fail"));
  if (type == initializeStepFail_)  return String(_T("initializeStep fail"));
  if (type == estimFail_)   return String(_T("Estimation fail"));
  if (type == mStepFail_)   return String(_T("mStep fail"));
  if (type == eStepFail_)   return String(_T("eStep fail"));
  if (type == mapStepFail_) return String(_T("mapStep fail"));
  if (type == cStepFail_)   return String(_T("cStep fail"));
  if (type == sStepFail_)   return String(_T("sStep fail"));
  return String(_T("unknown exception"));
}

References _T, STK::Clust::cStepFail_, STK::Clust::eStepFail_, STK::Clust::estimFail_, STK::Clust::initializeStepFail_, STK::Clust::mapStepFail_, STK::Clust::mStepFail_, STK::Clust::randomClassInitFail_, STK::Clust::randomFuzzyInitFail_, STK::Clust::randomInitFail_, STK::Clust::randomParamInitFail_, and STK::Clust::sStepFail_.

Referenced by STK::IMixtureAlgoPredict::burnStep(), STK::IMixtureAlgoPredict::predictBayesClassifier(), STK::EMAlgo::run(), STK::CEMAlgo::run(), STK::SEMAlgo::run(), STK::SemiSEMAlgo::run(), STK::ImputeAlgo::run(), STK::SimulAlgo::run(), STK::EMPredict::run(), STK::SemiSEMPredict::run(), STK::RandomInit::run(), STK::ClassInit::run(), and STK::FuzzyInit::run().

mixtureToMixtureClass()

MixtureClass STK::Clust::mixtureToMixtureClass

(

Mixture const &

type

)

convert a Mixture to a MixtureClass.

Parameters

type	the type of Mixture

Returns

the MixtureClass associated to this Mixture.

Definition at line 199 of file STK_Clust_Util.cpp.

{
  if (type == Gamma_ajk_bjk_)     return Gamma_;
  if (type == Gamma_ajk_bk_)      return Gamma_;
  if (type == Gamma_ajk_bj_)      return Gamma_;
  if (type == Gamma_ajk_b_)       return Gamma_;
  if (type == Gamma_ak_bjk_)      return Gamma_;
  if (type == Gamma_ak_bk_)       return Gamma_;
  if (type == Gamma_ak_bj_)       return Gamma_;
  if (type == Gamma_ak_b_)        return Gamma_;
  if (type == Gamma_aj_bjk_)      return Gamma_;
  if (type == Gamma_aj_bk_)       return Gamma_;
  if (type == Gamma_a_bjk_)       return Gamma_;
  if (type == Gamma_a_bk_)        return Gamma_;
  if (type == Gaussian_sjk_)      return DiagGaussian_;
  if (type == Gaussian_sk_)       return DiagGaussian_;
  if (type == Gaussian_sj_)       return DiagGaussian_;
  if (type == Gaussian_s_)        return DiagGaussian_;
  if (type == Gaussian_sjsk_)     return DiagGaussian_;
  if (type == HDGaussian_AjkBkQkDk_) return HDGaussian_;
  if (type == HDGaussian_AjkBkQkD_)  return HDGaussian_;
  if (type == HDGaussian_AjkBkQDk_)  return HDGaussian_;
  if (type == HDGaussian_AjkBkQD_)   return HDGaussian_;
  if (type == HDGaussian_AjkBQkDk_)  return HDGaussian_;
  if (type == HDGaussian_AjkBQkD_)   return HDGaussian_;
  if (type == HDGaussian_AjkBQDk_)   return HDGaussian_;
  if (type == HDGaussian_AjkBQD_)    return HDGaussian_;
  if (type == HDGaussian_AkBkQkDk_)  return HDGaussian_;
  if (type == HDGaussian_AkBkQkD_)   return HDGaussian_;
  if (type == HDGaussian_AkBkQDk_)   return HDGaussian_;
  if (type == HDGaussian_AkBkQD_)    return HDGaussian_;
  if (type == HDGaussian_AkBQkDk_)   return HDGaussian_;
  if (type == HDGaussian_AkBQkD_)    return HDGaussian_;
  if (type == HDGaussian_AkBQDk_)    return HDGaussian_;
  if (type == HDGaussian_AkBQD_)     return HDGaussian_;
  if (type == HDGaussian_AjBkQkDk_)  return HDGaussian_;
  if (type == HDGaussian_AjBkQkD_)   return HDGaussian_;
  if (type == HDGaussian_AjBkQDk_)   return HDGaussian_;
  if (type == HDGaussian_AjBkQD_)    return HDGaussian_;
  if (type == HDGaussian_AjBQkDk_)   return HDGaussian_;
  if (type == HDGaussian_AjBQkD_)    return HDGaussian_;
  if (type == HDGaussian_ABkQkDk_)   return HDGaussian_;
  if (type == HDGaussian_ABkQkD_)    return HDGaussian_;
  if (type == HDGaussian_ABkQDk_)    return HDGaussian_;
  if (type == HDGaussian_ABkQD_)     return HDGaussian_;
  if (type == HDGaussian_ABQkDk_)    return HDGaussian_;
  if (type == HDGaussian_ABQkD_)     return HDGaussian_;
  if (type == Categorical_pjk_)   return Categorical_;
  if (type == Categorical_pk_)    return Categorical_;
  if (type == Poisson_ljk_)       return Poisson_;
  if (type == Poisson_lk_)        return Poisson_;
  if (type == Poisson_ljlk_)      return Poisson_;
  if (type == Kmm_sk_) return Kmm_;
  if (type == Kmm_s_)  return Kmm_;
  if (type == unknown_mixture_)   return unknown_mixture_class_;
  return unknown_mixture_class_; // avoid compiler warning
}

References STK::Clust::Categorical_, STK::Clust::Categorical_pjk_, STK::Clust::Categorical_pk_, STK::Clust::DiagGaussian_, STK::Clust::Gamma_, STK::Clust::Gamma_a_bjk_, STK::Clust::Gamma_a_bk_, STK::Clust::Gamma_aj_bjk_, STK::Clust::Gamma_aj_bk_, STK::Clust::Gamma_ajk_b_, STK::Clust::Gamma_ajk_bj_, STK::Clust::Gamma_ajk_bjk_, STK::Clust::Gamma_ajk_bk_, STK::Clust::Gamma_ak_b_, STK::Clust::Gamma_ak_bj_, STK::Clust::Gamma_ak_bjk_, STK::Clust::Gamma_ak_bk_, STK::Clust::Gaussian_s_, STK::Clust::Gaussian_sj_, STK::Clust::Gaussian_sjk_, STK::Clust::Gaussian_sjsk_, STK::Clust::Gaussian_sk_, STK::Clust::HDGaussian_, STK::Clust::HDGaussian_ABkQD_, STK::Clust::HDGaussian_ABkQDk_, STK::Clust::HDGaussian_ABkQkD_, STK::Clust::HDGaussian_ABkQkDk_, STK::Clust::HDGaussian_ABQkD_, STK::Clust::HDGaussian_ABQkDk_, STK::Clust::HDGaussian_AjBkQD_, STK::Clust::HDGaussian_AjBkQDk_, STK::Clust::HDGaussian_AjBkQkD_, STK::Clust::HDGaussian_AjBkQkDk_, STK::Clust::HDGaussian_AjBQkD_, STK::Clust::HDGaussian_AjBQkDk_, STK::Clust::HDGaussian_AjkBkQD_, STK::Clust::HDGaussian_AjkBkQDk_, STK::Clust::HDGaussian_AjkBkQkD_, STK::Clust::HDGaussian_AjkBkQkDk_, STK::Clust::HDGaussian_AjkBQD_, STK::Clust::HDGaussian_AjkBQDk_, STK::Clust::HDGaussian_AjkBQkD_, STK::Clust::HDGaussian_AjkBQkDk_, STK::Clust::HDGaussian_AkBkQD_, STK::Clust::HDGaussian_AkBkQDk_, STK::Clust::HDGaussian_AkBkQkD_, STK::Clust::HDGaussian_AkBkQkDk_, STK::Clust::HDGaussian_AkBQD_, STK::Clust::HDGaussian_AkBQDk_, STK::Clust::HDGaussian_AkBQkD_, STK::Clust::HDGaussian_AkBQkDk_, STK::Clust::Kmm_, STK::Clust::Kmm_s_, STK::Clust::Kmm_sk_, STK::Clust::Poisson_, STK::Clust::Poisson_ljk_, STK::Clust::Poisson_ljlk_, STK::Clust::Poisson_lk_, STK::Clust::unknown_mixture_, and STK::Clust::unknown_mixture_class_.

Referenced by STK::MixtureComposerFacade< DataHandler_ >::getParameters(), and STK::MixtureComposerFacade< DataHandler_ >::setParameters().

mixtureToString() [1/2]

String STK::Clust::mixtureToString

(

Mixture const &

type

)

convert a Mixture to a String.

Parameters

type	the type of Mixture we want to convert

Returns

the string associated to this type.

Definition at line 453 of file STK_Clust_Util.cpp.

{
  if (type == Gamma_ajk_bjk_)     return String(_T("Gamma_ajk_bjk"));
  if (type == Gamma_ajk_bk_)      return String(_T("Gamma_ajk_bk"));
  if (type == Gamma_ajk_bj_)      return String(_T("Gamma_ajk_bj"));
  if (type == Gamma_ajk_b_)       return String(_T("Gamma_ajk_b"));
  if (type == Gamma_ak_bjk_)      return String(_T("Gamma_ak_bjk"));
  if (type == Gamma_ak_bk_)       return String(_T("Gamma_ak_bk"));
  if (type == Gamma_ak_bj_)       return String(_T("Gamma_ak_bj"));
  if (type == Gamma_ak_b_)        return String(_T("Gamma_ak_b"));
  if (type == Gamma_aj_bjk_)      return String(_T("Gamma_aj_bjk"));
  if (type == Gamma_aj_bk_)       return String(_T("Gamma_aj_bk"));
  if (type == Gamma_a_bjk_)       return String(_T("Gamma_a_bjk"));
  if (type == Gamma_a_bk_)        return String(_T("Gamma_a_bk"));
  if (type == Gaussian_sjk_)      return String(_T("Gaussian_sjk"));
  if (type == Gaussian_sk_)       return String(_T("Gaussian_sk"));
  if (type == Gaussian_sj_)       return String(_T("Gaussian_sj"));
  if (type == Gaussian_s_)        return String(_T("Gaussian_s"));
  if (type == Gaussian_sjsk_)     return String(_T("Gaussian_sjsk"));
  if (type == Categorical_pjk_)   return String(_T("Categorical_pjk"));
  if (type == Categorical_pk_)    return String(_T("Categorical_pk"));
  if (type == Poisson_ljk_)       return String(_T("Poisson_ljk"));
  if (type == Poisson_lk_)        return String(_T("Poisson_lk"));
  if (type == Poisson_ljlk_)      return String(_T("Poisson_ljlk"));
  if (type == Kmm_sk_)            return String(_T("Kmm_sk"));
  if (type == Kmm_s_)             return String(_T("Kmm_s"));
  if (type == HDGaussian_AjkBkQkDk_) return String(_T("HDGaussian_AjkBkQkDk"));
  if (type == HDGaussian_AjkBkQkD_)  return String(_T("HDGaussian_AjkBkQkD"));
  if (type == HDGaussian_AjkBkQDk_)  return String(_T("HDGaussian_AjkBkQDk"));
  if (type == HDGaussian_AjkBkQD_)   return String(_T("HDGaussian_AjkBkQD"));
  if (type == HDGaussian_AjkBQkDk_)  return String(_T("HDGaussian_AjkBQkDk"));
  if (type == HDGaussian_AjkBQkD_)   return String(_T("HDGaussian_AjkBQkD"));
  if (type == HDGaussian_AjkBQDk_)   return String(_T("HDGaussian_AjkBQDk"));
  if (type == HDGaussian_AjkBQD_)    return String(_T("HDGaussian_AjkBQD"));
  if (type == HDGaussian_AkBkQkDk_)  return String(_T("HDGaussian_AkBkQkDk"));
  if (type == HDGaussian_AkBkQkD_)   return String(_T("HDGaussian_AkBkQkD"));
  if (type == HDGaussian_AkBkQDk_)   return String(_T("HDGaussian_AkBkQDk"));
  if (type == HDGaussian_AkBkQD_)    return String(_T("HDGaussian_AkBkQD"));
  if (type == HDGaussian_AkBQkDk_)   return String(_T("HDGaussian_AkBQkDk"));
  if (type == HDGaussian_AkBQkD_)    return String(_T("HDGaussian_AkBQkD"));
  if (type == HDGaussian_AkBQDk_)    return String(_T("HDGaussian_AkBQDk"));
  if (type == HDGaussian_AkBQD_)     return String(_T("HDGaussian_AkBQD"));
  if (type == HDGaussian_AjBkQkDk_)  return String(_T("HDGaussian_AjBkQkDk"));
  if (type == HDGaussian_AjBkQkD_)   return String(_T("HDGaussian_AjBkQkD"));
  if (type == HDGaussian_AjBkQDk_)   return String(_T("HDGaussian_AjBkQDk"));
  if (type == HDGaussian_AjBkQD_)    return String(_T("HDGaussian_AjBkQD"));
  if (type == HDGaussian_AjBQkDk_)   return String(_T("HDGaussian_AjBQkDk"));
  if (type == HDGaussian_AjBQkD_)    return String(_T("HDGaussian_AjBQkD"));
  if (type == HDGaussian_ABkQkDk_)   return String(_T("HDGaussian_ABkQkDk"));
  if (type == HDGaussian_ABkQkD_)    return String(_T("HDGaussian_ABkQkD"));
  if (type == HDGaussian_ABkQDk_)    return String(_T("HDGaussian_ABkQDk"));
  if (type == HDGaussian_ABkQD_)     return String(_T("HDGaussian_ABkQD"));
  if (type == HDGaussian_ABQkDk_)    return String(_T("HDGaussian_ABQkDk"));
  if (type == HDGaussian_ABQkD_)     return String(_T("HDGaussian_ABQkD"));
  if (type == HDGaussian_ABQD_)      return String(_T("HDGaussian_ABQD"));
  return String(_T("unknown"));
}

References _T, STK::Clust::Categorical_pjk_, STK::Clust::Categorical_pk_, STK::Clust::Gamma_a_bjk_, STK::Clust::Gamma_a_bk_, STK::Clust::Gamma_aj_bjk_, STK::Clust::Gamma_aj_bk_, STK::Clust::Gamma_ajk_b_, STK::Clust::Gamma_ajk_bj_, STK::Clust::Gamma_ajk_bjk_, STK::Clust::Gamma_ajk_bk_, STK::Clust::Gamma_ak_b_, STK::Clust::Gamma_ak_bj_, STK::Clust::Gamma_ak_bjk_, STK::Clust::Gamma_ak_bk_, STK::Clust::Gaussian_s_, STK::Clust::Gaussian_sj_, STK::Clust::Gaussian_sjk_, STK::Clust::Gaussian_sjsk_, STK::Clust::Gaussian_sk_, STK::Clust::HDGaussian_ABkQD_, STK::Clust::HDGaussian_ABkQDk_, STK::Clust::HDGaussian_ABkQkD_, STK::Clust::HDGaussian_ABkQkDk_, STK::Clust::HDGaussian_ABQD_, STK::Clust::HDGaussian_ABQkD_, STK::Clust::HDGaussian_ABQkDk_, STK::Clust::HDGaussian_AjBkQD_, STK::Clust::HDGaussian_AjBkQDk_, STK::Clust::HDGaussian_AjBkQkD_, STK::Clust::HDGaussian_AjBkQkDk_, STK::Clust::HDGaussian_AjBQkD_, STK::Clust::HDGaussian_AjBQkDk_, STK::Clust::HDGaussian_AjkBkQD_, STK::Clust::HDGaussian_AjkBkQDk_, STK::Clust::HDGaussian_AjkBkQkD_, STK::Clust::HDGaussian_AjkBkQkDk_, STK::Clust::HDGaussian_AjkBQD_, STK::Clust::HDGaussian_AjkBQDk_, STK::Clust::HDGaussian_AjkBQkD_, STK::Clust::HDGaussian_AjkBQkDk_, STK::Clust::HDGaussian_AkBkQD_, STK::Clust::HDGaussian_AkBkQDk_, STK::Clust::HDGaussian_AkBkQkD_, STK::Clust::HDGaussian_AkBkQkDk_, STK::Clust::HDGaussian_AkBQD_, STK::Clust::HDGaussian_AkBQDk_, STK::Clust::HDGaussian_AkBQkD_, STK::Clust::HDGaussian_AkBQkDk_, STK::Clust::Kmm_s_, STK::Clust::Kmm_sk_, STK::Clust::Poisson_ljk_, STK::Clust::Poisson_ljlk_, and STK::Clust::Poisson_lk_.

mixtureToString() [2/2]

String STK::Clust::mixtureToString	(	Mixture	type,
		bool	freeProp
	)

convert a Mixture to a string specifying if the model is with free proportions.

See also

stringToMixture

Parameters

type	the Mixture we want to convert
freeProp	true if the model have free proportions, false otherwise.

Returns

the string represented by the Mixture type.

Definition at line 519 of file STK_Clust_Util.cpp.

{
  if (freeProp == false)
  {
    if (type == Gamma_ajk_bjk_)     return String(_T("Gamma_p_ajk_bjk"));
    if (type == Gamma_ajk_bk_)      return String(_T("Gamma_p_ajk_bk"));
    if (type == Gamma_ajk_bj_)      return String(_T("Gamma_p_ajk_bj"));
    if (type == Gamma_ajk_b_)       return String(_T("Gamma_p_ajk_b"));
    if (type == Gamma_ak_bjk_)      return String(_T("Gamma_p_ak_bjk"));
    if (type == Gamma_ak_bk_)       return String(_T("Gamma_p_ak_bk"));
    if (type == Gamma_ak_bj_)       return String(_T("Gamma_p_ak_bj"));
    if (type == Gamma_ak_b_)        return String(_T("Gamma_p_ak_b"));
    if (type == Gamma_aj_bjk_)      return String(_T("Gamma_p_aj_bjk"));
    if (type == Gamma_aj_bk_)       return String(_T("Gamma_p_aj_bk"));
    if (type == Gamma_a_bjk_)       return String(_T("Gamma_p_a_bjk"));
    if (type == Gamma_a_bk_)        return String(_T("Gamma_p_a_bk"));
    if (type == Gaussian_sjk_)      return String(_T("Gaussian_p_sjk"));
    if (type == Gaussian_sk_)       return String(_T("Gaussian_p_sk"));
    if (type == Gaussian_sj_)       return String(_T("Gaussian_p_sj"));
    if (type == Gaussian_s_)        return String(_T("Gaussian_p_s"));
    if (type == Gaussian_sjsk_)     return String(_T("Gaussian_p_sjsk"));
    if (type == Categorical_pjk_)   return String(_T("Categorical_p_pjk"));
    if (type == Categorical_pk_)    return String(_T("Categorical_p_pk"));
    if (type == Poisson_ljk_)       return String(_T("Poisson_p_ljk"));
    if (type == Poisson_lk_)        return String(_T("Poisson_p_lk"));
    if (type == Poisson_ljlk_)      return String(_T("Poisson_p_ljlk"));
    if (type == Poisson_ljlk_)      return String(_T("Poisson_p_ljlk"));
    if (type == Kmm_sk_)            return String(_T("Kmm_p_sk"));
    if (type == Kmm_s_)             return String(_T("Kmm_p_s"));
    if (type == HDGaussian_AjkBkQkDk_) return String(_T("HDGaussian_p_AjkBkQkDk"));
    if (type == HDGaussian_AjkBkQkD_)  return String(_T("HDGaussian_p_AjkBkQkD"));
    if (type == HDGaussian_AjkBkQDk_)  return String(_T("HDGaussian_p_AjkBkQDk"));
    if (type == HDGaussian_AjkBkQD_)   return String(_T("HDGaussian_p_AjkBkQD"));
    if (type == HDGaussian_AjkBQkDk_)  return String(_T("HDGaussian_p_AjkBQkDk"));
    if (type == HDGaussian_AjkBQkD_)   return String(_T("HDGaussian_p_AjkBQkD"));
    if (type == HDGaussian_AjkBQDk_)   return String(_T("HDGaussian_p_AjkBQDk"));
    if (type == HDGaussian_AjkBQD_)    return String(_T("HDGaussian_p_AjkBQD"));
    if (type == HDGaussian_AkBkQkDk_)  return String(_T("HDGaussian_p_AkBkQkDk"));
    if (type == HDGaussian_AkBkQkD_)   return String(_T("HDGaussian_p_AkBkQkD"));
    if (type == HDGaussian_AkBkQDk_)   return String(_T("HDGaussian_p_AkBkQDk"));
    if (type == HDGaussian_AkBkQD_)    return String(_T("HDGaussian_p_AkBkQD"));
    if (type == HDGaussian_AkBQkDk_)   return String(_T("HDGaussian_p_AkBQkDk"));
    if (type == HDGaussian_AkBQkD_)    return String(_T("HDGaussian_p_AkBQkD"));
    if (type == HDGaussian_AkBQDk_)    return String(_T("HDGaussian_p_AkBQDk"));
    if (type == HDGaussian_AkBQD_)     return String(_T("HDGaussian_p_AkBQD"));
    if (type == HDGaussian_AjBkQkDk_)  return String(_T("HDGaussian_p_AjBkQkDk"));
    if (type == HDGaussian_AjBkQkD_)   return String(_T("HDGaussian_p_AjBkQkD"));
    if (type == HDGaussian_AjBkQDk_)   return String(_T("HDGaussian_p_AjBkQDk"));
    if (type == HDGaussian_AjBkQD_)    return String(_T("HDGaussian_p_AjBkQD"));
    if (type == HDGaussian_AjBQkDk_)   return String(_T("HDGaussian_p_AjBQkDk"));
    if (type == HDGaussian_AjBQkD_)    return String(_T("HDGaussian_p_AjBQkD"));
    if (type == HDGaussian_ABkQkDk_)   return String(_T("HDGaussian_p_ABkQkDk"));
    if (type == HDGaussian_ABkQkD_)    return String(_T("HDGaussian_p_ABkQkD"));
    if (type == HDGaussian_ABkQDk_)    return String(_T("HDGaussian_p_ABkQDk"));
    if (type == HDGaussian_ABkQD_)     return String(_T("HDGaussian_p_ABkQD"));
    if (type == HDGaussian_ABQkDk_)    return String(_T("HDGaussian_p_ABQkDk"));
    if (type == HDGaussian_ABQkD_)     return String(_T("HDGaussian_p_ABQkD"));
    if (type == HDGaussian_ABQD_)     return String(_T("HDGaussian_p_ABQD"));
  }
  else
  {
    if (type == Gamma_ajk_bjk_)     return String(_T("Gamma_pk_ajk_bjk"));
    if (type == Gamma_ajk_bk_)      return String(_T("Gamma_pk_ajk_bk"));
    if (type == Gamma_ajk_bj_)      return String(_T("Gamma_pk_ajk_bj"));
    if (type == Gamma_ajk_b_)       return String(_T("Gamma_pk_ajk_b"));
    if (type == Gamma_ak_bjk_)      return String(_T("Gamma_pk_ak_bjk"));
    if (type == Gamma_ak_bk_)       return String(_T("Gamma_pk_ak_bk"));
    if (type == Gamma_ak_bj_)       return String(_T("Gamma_pk_ak_bj"));
    if (type == Gamma_ak_b_)        return String(_T("Gamma_pk_ak_b"));
    if (type == Gamma_aj_bjk_)      return String(_T("Gamma_pk_aj_bjk"));
    if (type == Gamma_aj_bk_)       return String(_T("Gamma_pk_aj_bk"));
    if (type == Gamma_a_bjk_)       return String(_T("Gamma_pk_a_bjk"));
    if (type == Gamma_a_bk_)        return String(_T("Gamma_pk_a_bk"));
    if (type == Gaussian_sjk_)      return String(_T("Gaussian_pk_sjk"));
    if (type == Gaussian_sk_)       return String(_T("Gaussian_pk_sk"));
    if (type == Gaussian_sj_)       return String(_T("Gaussian_pk_sj"));
    if (type == Gaussian_s_)        return String(_T("Gaussian_pk_s"));
    if (type == Gaussian_sjsk_)     return String(_T("Gaussian_pk_sjsk"));
    if (type == Categorical_pjk_)   return String(_T("Categorical_pk_pjk"));
    if (type == Categorical_pk_)    return String(_T("Categorical_pk_pk"));
    if (type == Poisson_ljk_)       return String(_T("Poisson_pk_ljk"));
    if (type == Poisson_lk_)        return String(_T("Poisson_pk_lk"));
    if (type == Poisson_ljlk_)      return String(_T("Poisson_pk_ljlk"));
    if (type == Kmm_sk_)            return String(_T("Kmm_pk_sk"));
    if (type == Kmm_s_)             return String(_T("Kmm_pk_s"));
    if (type == HDGaussian_AjkBkQkDk_) return String(_T("HDGaussian_pk_AjkBkQkDk"));
    if (type == HDGaussian_AjkBkQkD_)  return String(_T("HDGaussian_pk_AjkBkQkD"));
    if (type == HDGaussian_AjkBkQDk_)  return String(_T("HDGaussian_pk_AjkBkQDk"));
    if (type == HDGaussian_AjkBkQD_)   return String(_T("HDGaussian_pk_AjkBkQD"));
    if (type == HDGaussian_AjkBQkDk_)  return String(_T("HDGaussian_pk_AjkBQkDk"));
    if (type == HDGaussian_AjkBQkD_)   return String(_T("HDGaussian_pk_AjkBQkD"));
    if (type == HDGaussian_AjkBQDk_)   return String(_T("HDGaussian_pk_AjkBQDk"));
    if (type == HDGaussian_AjkBQD_)    return String(_T("HDGaussian_pk_AjkBQD"));
    if (type == HDGaussian_AkBkQkDk_)  return String(_T("HDGaussian_pk_AkBkQkDk"));
    if (type == HDGaussian_AkBkQkD_)   return String(_T("HDGaussian_pk_AkBkQkD"));
    if (type == HDGaussian_AkBkQDk_)   return String(_T("HDGaussian_pk_AkBkQDk"));
    if (type == HDGaussian_AkBkQD_)    return String(_T("HDGaussian_pk_AkBkQD"));
    if (type == HDGaussian_AkBQkDk_)   return String(_T("HDGaussian_pk_AkBQkDk"));
    if (type == HDGaussian_AkBQkD_)    return String(_T("HDGaussian_pk_AkBQkD"));
    if (type == HDGaussian_AkBQDk_)    return String(_T("HDGaussian_pk_AkBQDk"));
    if (type == HDGaussian_AkBQD_)     return String(_T("HDGaussian_pk_AkBQD"));
    if (type == HDGaussian_AjBkQkDk_)  return String(_T("HDGaussian_pk_AjBkQkDk"));
    if (type == HDGaussian_AjBkQkD_)   return String(_T("HDGaussian_pk_AjBkQkD"));
    if (type == HDGaussian_AjBkQDk_)   return String(_T("HDGaussian_pk_AjBkQDk"));
    if (type == HDGaussian_AjBkQD_)    return String(_T("HDGaussian_pk_AjBkQD"));
    if (type == HDGaussian_AjBQkDk_)   return String(_T("HDGaussian_pk_AjBQkDk"));
    if (type == HDGaussian_AjBQkD_)    return String(_T("HDGaussian_pk_AjBQkD"));
    if (type == HDGaussian_ABkQkDk_)   return String(_T("HDGaussian_pk_ABkQkDk"));
    if (type == HDGaussian_ABkQkD_)    return String(_T("HDGaussian_pk_ABkQkD"));
    if (type == HDGaussian_ABkQDk_)    return String(_T("HDGaussian_pk_ABkQDk"));
    if (type == HDGaussian_ABkQD_)     return String(_T("HDGaussian_pk_ABkQD"));
    if (type == HDGaussian_ABQkDk_)    return String(_T("HDGaussian_pk_ABQkDk"));
    if (type == HDGaussian_ABQkD_)     return String(_T("HDGaussian_pk_ABQkD"));
    if (type == HDGaussian_ABQD_)      return String(_T("HDGaussian_pk_ABQD"));
  }
  return String(_T("unknown"));
}

References _T, STK::Clust::Categorical_pjk_, STK::Clust::Categorical_pk_, STK::Clust::Gamma_a_bjk_, STK::Clust::Gamma_a_bk_, STK::Clust::Gamma_aj_bjk_, STK::Clust::Gamma_aj_bk_, STK::Clust::Gamma_ajk_b_, STK::Clust::Gamma_ajk_bj_, STK::Clust::Gamma_ajk_bjk_, STK::Clust::Gamma_ajk_bk_, STK::Clust::Gamma_ak_b_, STK::Clust::Gamma_ak_bj_, STK::Clust::Gamma_ak_bjk_, STK::Clust::Gamma_ak_bk_, STK::Clust::Gaussian_s_, STK::Clust::Gaussian_sj_, STK::Clust::Gaussian_sjk_, STK::Clust::Gaussian_sjsk_, STK::Clust::Gaussian_sk_, STK::Clust::HDGaussian_ABkQD_, STK::Clust::HDGaussian_ABkQDk_, STK::Clust::HDGaussian_ABkQkD_, STK::Clust::HDGaussian_ABkQkDk_, STK::Clust::HDGaussian_ABQD_, STK::Clust::HDGaussian_ABQkD_, STK::Clust::HDGaussian_ABQkDk_, STK::Clust::HDGaussian_AjBkQD_, STK::Clust::HDGaussian_AjBkQDk_, STK::Clust::HDGaussian_AjBkQkD_, STK::Clust::HDGaussian_AjBkQkDk_, STK::Clust::HDGaussian_AjBQkD_, STK::Clust::HDGaussian_AjBQkDk_, STK::Clust::HDGaussian_AjkBkQD_, STK::Clust::HDGaussian_AjkBkQDk_, STK::Clust::HDGaussian_AjkBkQkD_, STK::Clust::HDGaussian_AjkBkQkDk_, STK::Clust::HDGaussian_AjkBQD_, STK::Clust::HDGaussian_AjkBQDk_, STK::Clust::HDGaussian_AjkBQkD_, STK::Clust::HDGaussian_AjkBQkDk_, STK::Clust::HDGaussian_AkBkQD_, STK::Clust::HDGaussian_AkBkQDk_, STK::Clust::HDGaussian_AkBkQkD_, STK::Clust::HDGaussian_AkBkQkDk_, STK::Clust::HDGaussian_AkBQD_, STK::Clust::HDGaussian_AkBQDk_, STK::Clust::HDGaussian_AkBQkD_, STK::Clust::HDGaussian_AkBQkDk_, STK::Clust::Kmm_s_, STK::Clust::Kmm_sk_, STK::Clust::Poisson_ljk_, STK::Clust::Poisson_ljlk_, and STK::Clust::Poisson_lk_.

stringToAlgo()

algoType STK::Clust::stringToAlgo

(

String const &

type

)

Convert a String to an algoType.

The recognized strings are

Algorithm
"emAlgo"
"cemAlgo"
"semAlgo"
"semiSemAlgo"
"em"
"cem"
"sem"
"semiSem"

Parameters

type	the type of algorithm wanted

Returns

the algoType corresponding (default is emAlgo)

Note

The capitalized letters have no effect and if the string is not found in the list above, the type Clust::emAlgo_ is returned.

Definition at line 93 of file STK_Clust_Util.cpp.

{
  if (toUpperString(type) == toUpperString(_T("emAlgo"))) return emAlgo_;
  if (toUpperString(type) == toUpperString(_T("cemAlgo"))) return cemAlgo_;
  if (toUpperString(type) == toUpperString(_T("semAlgo"))) return semAlgo_;
  if (toUpperString(type) == toUpperString(_T("semiSemAlgo"))) return semiSemAlgo_;
  if (toUpperString(type) == toUpperString(_T("em"))) return emAlgo_;
  if (toUpperString(type) == toUpperString(_T("cem"))) return cemAlgo_;
  if (toUpperString(type) == toUpperString(_T("sem"))) return semAlgo_;
  if (toUpperString(type) == toUpperString(_T("semiSem"))) return semiSemAlgo_;
  return emAlgo_;
}

References _T, STK::Clust::cemAlgo_, STK::Clust::emAlgo_, STK::Clust::semAlgo_, STK::Clust::semiSemAlgo_, and STK::toUpperString().

stringToCriterion()

criterionType STK::Clust::stringToCriterion

(

String const &

type

)

Convert a String to an criterionType.

The recognized strings are

Criterion
"AIC"
"BIC"
"ICL </td></tr> <tr> <td> "ML"

Parameters

type	the type of criterion wanted

Returns

the criterionType corresponding

Note

The capitalized letters have no effect and if the string is not found in the list above,the type Clust::bic_ is returned.

Definition at line 164 of file STK_Clust_Util.cpp.

{
  if (toUpperString(type) == toUpperString(_T("AIC"))) return aic_;
  if (toUpperString(type) == toUpperString(_T("BIC"))) return bic_;
  if (toUpperString(type) == toUpperString(_T("ICL"))) return icl_;
  if (toUpperString(type) == toUpperString(_T("ML"))) return ml_;
  return bic_;
}

References _T, STK::Clust::aic_, STK::Clust::bic_, STK::Clust::icl_, STK::Clust::ml_, and STK::toUpperString().

Referenced by STK::Clust::createCriterion().

stringToInit()

initType STK::Clust::stringToInit

(

String const &

type

)

Convert a String to a initType.

The recognized strings are

Initialization
"randomInit" (DEPECATED)
"randomParamInit"
"randomClassInit"
"randomFuzzyInit"
"random"
"class"
"fuzzy"

Parameters

type	the type of initialization wanted

Returns

the initType corresponding (default is randomClassInit)

Note

if the string is not found in the list above,the type Clust::randomClassInit_ is returned.

Definition at line 65 of file STK_Clust_Util.cpp.

{
  if (toUpperString(type) == toUpperString(_T("randomInit"))) return randomParamInit_;
  if (toUpperString(type) == toUpperString(_T("randomParamInit"))) return randomParamInit_;
  if (toUpperString(type) == toUpperString(_T("randomClassInit"))) return randomClassInit_;
  if (toUpperString(type) == toUpperString(_T("randomFuzzyInit"))) return randomFuzzyInit_;
  if (toUpperString(type) == toUpperString(_T("random"))) return randomParamInit_;
  if (toUpperString(type) == toUpperString(_T("class"))) return randomClassInit_;
  if (toUpperString(type) == toUpperString(_T("fuzzy"))) return randomFuzzyInit_;
  return randomClassInit_;
}

References _T, STK::Clust::randomClassInit_, STK::Clust::randomFuzzyInit_, STK::Clust::randomParamInit_, and STK::toUpperString().

stringToLearnAlgo()

algoLearnType STK::Clust::stringToLearnAlgo

(

String const &

type

)

Convert a String to an algoLearnType.

The recognized strings are

Algorithm
"imputeAlgo"
"simulAlgo"
"impute"
"simul"

Parameters

type	the type of algorithm wanted

Returns

the algoType corresponding (default is emAlgo)

Note

The capitalized letters have no effect and if the string is not found in the list above,the type Clust::emAlgo_ is returned.

Definition at line 139 of file STK_Clust_Util.cpp.

{
  if (toUpperString(type) == toUpperString(_T("imputeAlgo"))) return imputeAlgo_;
  if (toUpperString(type) == toUpperString(_T("simulAlgo"))) return simulAlgo_;
  if (toUpperString(type) == toUpperString(_T("impute"))) return imputeAlgo_;
  if (toUpperString(type) == toUpperString(_T("simul"))) return simulAlgo_;
  return imputeAlgo_;
}

References _T, STK::Clust::imputeAlgo_, STK::Clust::simulAlgo_, and STK::toUpperString().

stringToMixture() [1/2]

Mixture STK::Clust::stringToMixture

(

String const &

type

)

Convert a String to a Mixture.

The recognized strings are

Model
"Gamma_Ajkbjk"
"Gamma_Ajkbk"
"Gamma_Ajkbj"
"Gamma_Ajkb"
"Gamma_ak_bjk"
"Gamma_ak_bk"
"Gamma_ak_bj"
"Gamma_ak_b"
"Gamma_aj_bjk"
"Gamma_aj_bk"
"Gamma_a_bjk"
"Gamma_a_bk"
"Gaussian_sjk"
"Gaussian_sk"
"Gaussian_sj"
"Gaussian_s"
"Gaussian_sjsk"
"HDGaussian_AjkBkQkDk"
"HDGaussian_AjkBkQkD"
"HDGaussian_AjkBkQdk"
"HDGaussian_AjkBkQd"
"HDGaussian_AjkBQkDk"
"HDGaussian_AjkBQkD"
"HDGaussian_AjkBQdk"
"HDGaussian_AjkBQd"
"HDGaussian_AkBkQkDk"
"HDGaussian_AkBkQkD"
"HDGaussian_AkBkQdk"
"HDGaussian_AkBkQd"
"HDGaussian_AkBQkDk"
"HDGaussian_AkBQkD"
"HDGaussian_AkBQdk"
"HDGaussian_AkBQd"
"HDGaussian_AjBkQkDk"
"HDGaussian_AjBkQkD"
"HDGaussian_AjBkQdk"
"HDGaussian_AjBkQd"
"HDGaussian_AjBQkDk"
"HDGaussian_AjBQkD"
"HDGaussian_ABkQkDk"
"HDGaussian_ABkQkD"
"HDGaussian_ABkQdk"
"HDGaussian_ABkQd,"
"HDGaussian_ABQkDk"
"HDGaussian_ABQkD"
"HDGaussian_ABQD"
"Categorical_pjk"
"Categorical_pk"
"Poisson_ljk"
"Poisson_lk"
"Poisson_ljlk"
"Kmm_sk"
"Kmm_s"

Parameters

type	the String we want to convert

Returns

the Mixture represented by the String type. if the string does not match any known name, the unknown_mixture_ type is returned.

Definition at line 263 of file STK_Clust_Util.cpp.

{
  if (toUpperString(type) == toUpperString(_T("Gamma_ajk_bjk")))    return Gamma_ajk_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_ajk_bk")))     return Gamma_ajk_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_ajk_bj")))     return Gamma_ajk_bj_;
  if (toUpperString(type) == toUpperString(_T("Gamma_ajk_b")))      return Gamma_ajk_b_;
  if (toUpperString(type) == toUpperString(_T("Gamma_ak_bjk")))     return Gamma_ak_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_ak_bk")))      return Gamma_ak_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_ak_bj")))      return Gamma_ak_bj_;
  if (toUpperString(type) == toUpperString(_T("Gamma_ak_b")))       return Gamma_ak_b_;
  if (toUpperString(type) == toUpperString(_T("Gamma_aj_bjk")))     return Gamma_aj_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_aj_bk")))      return Gamma_aj_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_a_bjk")))      return Gamma_a_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_a_bk")))       return Gamma_a_bk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_sjk")))     return Gaussian_sjk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_sk")))      return Gaussian_sk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_sj")))      return Gaussian_sj_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_s")))       return Gaussian_s_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_sjsk")))    return Gaussian_sjsk_;
  if (toUpperString(type) == toUpperString(_T("Categorical_pjk")))  return Categorical_pjk_;
  if (toUpperString(type) == toUpperString(_T("Categorical_pk")))   return Categorical_pk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_ljk")))      return Poisson_ljk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_lk")))       return Poisson_lk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_ljlk")))     return Poisson_ljlk_;
  if (toUpperString(type) == toUpperString(_T("Kmm_sk")))return Kmm_sk_;
  if (toUpperString(type) == toUpperString(_T("Kmm_s"))) return Kmm_s_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBkQkDk")))return HDGaussian_AjkBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBkQkD"))) return HDGaussian_AjkBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBkQDk"))) return HDGaussian_AjkBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBkQD")))  return HDGaussian_AjkBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBQkDk"))) return HDGaussian_AjkBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBQkD")))  return HDGaussian_AjkBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBQDk")))  return HDGaussian_AjkBQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjkBQD")))   return HDGaussian_AjkBQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBkQkDk"))) return HDGaussian_AkBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBkQkD")))  return HDGaussian_AkBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBkQDk")))  return HDGaussian_AkBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBkQD")))   return HDGaussian_AkBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBQkDk")))  return HDGaussian_AkBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBQkD")))   return HDGaussian_AkBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBQDk")))   return HDGaussian_AkBQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AkBQD")))    return HDGaussian_AkBQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjBkQkDk"))) return HDGaussian_AjBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjBkQkD")))  return HDGaussian_AjBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjBkQDk")))  return HDGaussian_AjBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjBkQD")))   return HDGaussian_AjBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjBQkDk")))  return HDGaussian_AjBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_AjBQkD")))   return HDGaussian_AjBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_ABkQkDk")))  return HDGaussian_ABkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_ABkQkD")))   return HDGaussian_ABkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_ABkQDk")))   return HDGaussian_ABkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_ABkQD")))    return HDGaussian_ABkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_ABQkDk")))   return HDGaussian_ABQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_ABQkD")))    return HDGaussian_ABQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_ABQD")))     return HDGaussian_ABQD_;
  // try second naming sheme
  bool freeProp;
  Mixture res = stringToMixture(type, freeProp);
#ifdef STK_MIXTURE_DEBUG
  if (res == unknown_mixture_)
  { stk_cout << _T("In stringToMixture, mixture ") << type << _T(" not found.\n");}
#endif
  return res;
}

References _T, STK::Clust::Categorical_pjk_, STK::Clust::Categorical_pk_, STK::Clust::Gamma_a_bjk_, STK::Clust::Gamma_a_bk_, STK::Clust::Gamma_aj_bjk_, STK::Clust::Gamma_aj_bk_, STK::Clust::Gamma_ajk_b_, STK::Clust::Gamma_ajk_bj_, STK::Clust::Gamma_ajk_bjk_, STK::Clust::Gamma_ajk_bk_, STK::Clust::Gamma_ak_b_, STK::Clust::Gamma_ak_bj_, STK::Clust::Gamma_ak_bjk_, STK::Clust::Gamma_ak_bk_, STK::Clust::Gaussian_s_, STK::Clust::Gaussian_sj_, STK::Clust::Gaussian_sjk_, STK::Clust::Gaussian_sjsk_, STK::Clust::Gaussian_sk_, STK::Clust::HDGaussian_ABkQD_, STK::Clust::HDGaussian_ABkQDk_, STK::Clust::HDGaussian_ABkQkD_, STK::Clust::HDGaussian_ABkQkDk_, STK::Clust::HDGaussian_ABQD_, STK::Clust::HDGaussian_ABQkD_, STK::Clust::HDGaussian_ABQkDk_, STK::Clust::HDGaussian_AjBkQD_, STK::Clust::HDGaussian_AjBkQDk_, STK::Clust::HDGaussian_AjBkQkD_, STK::Clust::HDGaussian_AjBkQkDk_, STK::Clust::HDGaussian_AjBQkD_, STK::Clust::HDGaussian_AjBQkDk_, STK::Clust::HDGaussian_AjkBkQD_, STK::Clust::HDGaussian_AjkBkQDk_, STK::Clust::HDGaussian_AjkBkQkD_, STK::Clust::HDGaussian_AjkBkQkDk_, STK::Clust::HDGaussian_AjkBQD_, STK::Clust::HDGaussian_AjkBQDk_, STK::Clust::HDGaussian_AjkBQkD_, STK::Clust::HDGaussian_AjkBQkDk_, STK::Clust::HDGaussian_AkBkQD_, STK::Clust::HDGaussian_AkBkQDk_, STK::Clust::HDGaussian_AkBkQkD_, STK::Clust::HDGaussian_AkBkQkDk_, STK::Clust::HDGaussian_AkBQD_, STK::Clust::HDGaussian_AkBQDk_, STK::Clust::HDGaussian_AkBQkD_, STK::Clust::HDGaussian_AkBQkDk_, STK::Clust::Kmm_s_, STK::Clust::Kmm_sk_, STK::Clust::Poisson_ljk_, STK::Clust::Poisson_ljlk_, STK::Clust::Poisson_lk_, stk_cout, STK::Clust::stringToMixture(), STK::toUpperString(), and STK::Clust::unknown_mixture_.

Referenced by STK::CategoricalMixtureManager< DataHandler >::createMixtureImpl(), STK::DiagGaussianMixtureManager< DataHandler >::createMixtureImpl(), STK::GammaMixtureManager< DataHandler >::createMixtureImpl(), STK::KernelMixtureManager::createMixtureImpl(), STK::PoissonMixtureManager< DataHandler >::createMixtureImpl(), STK::IMixtureManager< Derived >::getIdModel(), STK::MixtureComposerFacade< DataHandler_ >::getParameters(), STK::MixtureComposerFacade< DataHandler_ >::setParameters(), and STK::Clust::stringToMixture().

stringToMixture() [2/2]

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.

The recognized strings are

Free proportions	Fixed Proportions
"Gamma_pk_ajk_bjk"	"Gamma_p_ajk_bjk"
"Gamma_pk_ajk_bk"	"Gamma_p_ajk_bk"
"Gamma_pk_ajk_bj"	"Gamma_p_ajk_bj"
"Gamma_pk_ajk_b"	"Gamma_p_ajk_b"
"Gamma_pk_ak_bjk"	"Gamma_p_ak_bjk"
"Gamma_pk_ak_bk"	"Gamma_p_ak_bk"
"Gamma_pk_ak_bj"	"Gamma_p_ak_bj"
"Gamma_pk_ak_b"	"Gamma_p_ak_b"
"Gamma_pk_aj_bjk"	"Gamma_p_aj_bjk"
"Gamma_pk_aj_bk"	"Gamma_p_aj_bk"
"Gamma_pk_a_bjk"	"Gamma_p_a_bjk"
"Gamma_pk_a_bk"	"Gamma_p_a_bk"
"Gaussian_pk_sjk"	"Gaussian_p_sjk"
"Gaussian_pk_sk"	"Gaussian_p_sk"
"Gaussian_pk_sj"	"Gaussian_p_sj"
"Gaussian_pk_s"	"Gaussian_p_s"
"Gaussian_pk_sjsk"	"Gaussian_p_sjsk"
"HDGaussian_pk_AjkBkQkDk"	"HDGaussian_p_AjkBkQkDk"
"HDGaussian_pk_AjkBkQkD"	"HDGaussian_p_AjkBkQkD"
"HDGaussian_pk_AjkBkQdk"	"HDGaussian_p_AjkBkQdk"
"HDGaussian_pk_AjkBkQd"	"HDGaussian_p_AjkBkQd"
"HDGaussian_pk_AjkBQkDk"	"HDGaussian_p_AjkBQkDk"
"HDGaussian_pk_AjkBQkD"	"HDGaussian_p_AjkBQkD"
"HDGaussian_pk_AjkBQdk"	"HDGaussian_p_AjkBQdk"
"HDGaussian_pk_AjkBQd"	"HDGaussian_p_AjkBQd"
"HDGaussian_pk_AkBkQkDk"	"HDGaussian_p_AkBkQkDk"
"HDGaussian_pk_AkBkQkD"	"HDGaussian_p_AkBkQkD"
"HDGaussian_pk_AkBkQdk"	"HDGaussian_p_AkBkQdk"
"HDGaussian_pk_AkBkQd"	"HDGaussian_p_AkBkQd"
"HDGaussian_pk_AkBQkDk"	"HDGaussian_p_AkBQkDk"
"HDGaussian_pk_AkBQkD"	"HDGaussian_p_AkBQkD"
"HDGaussian_pk_AkBQdk"	"HDGaussian_p_AkBQdk"
"HDGaussian_pk_AkBQd"	"HDGaussian_p_AkBQd"
"HDGaussian_pk_AjBkQkDk"	"HDGaussian_p_AjBkQkDk"
"HDGaussian_pk_AjBkQkD"	"HDGaussian_p_AjBkQkD"
"HDGaussian_pk_AjBkQdk"	"HDGaussian_p_AjBkQdk"
"HDGaussian_pk_AjBkQd"	"HDGaussian_p_AjBkQd"
"HDGaussian_pk_AjBQkDk"	"HDGaussian_p_AjBQkDk"
"HDGaussian_pk_AjBQkD"	"HDGaussian_p_AjBQkD"
"HDGaussian_pk_ABkQkDk"	"HDGaussian_p_ABkQkDk"
"HDGaussian_pk_ABkQkD"	"HDGaussian_p_ABkQkD"
"HDGaussian_pk_ABkQdk"	"HDGaussian_p_ABkQdk"
"HDGaussian_pk_ABkQd,"	"HDGaussian_p_ABkQd,"
"HDGaussian_pk_ABQkDk"	"HDGaussian_p_ABQkDk"
"HDGaussian_pk_ABQkD"	"HDGaussian_p_ABQkD"
"HDGaussian_pk_ABQD"	"HDGaussian_p_ABQD"
"Categorical_pk_pjk"	"Categorical_p_pjk"
"Categorical_pk_pk"	"Categorical_p_pk"
"Poisson_pk_ljk"	"Poisson_p_ljk"
"Poisson_pk_lk"	"Poisson_p_lk"
"Poisson_pk_ljlk"	"Poisson_p_ljlk"
"Kmm_pk_sk"	"Kmm_p_sk"
"Kmm_pk_s"	"Kmm_p_s"

Parameters

	type	the String we want to convert
[out]	freeProp	true if the model have free proportions, false otherwise.

Returns

the Mixture represented by the String type. if the string does not match any known name, the unknown_mixture_ type is returned.

Definition at line 333 of file STK_Clust_Util.cpp.

{
  freeProp = false;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ajk_bjk"))) return Gamma_ajk_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ajk_bk")))  return Gamma_ajk_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ajk_bj")))  return Gamma_ajk_bj_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ajk_b")))   return Gamma_ajk_b_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ak_bjk")))  return Gamma_ak_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ak_bk")))   return Gamma_ak_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ak_bj")))   return Gamma_ak_bj_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_ak_b")))    return Gamma_ak_b_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_aj_bjk")))  return Gamma_aj_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_aj_bk")))   return Gamma_aj_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_a_bjk")))   return Gamma_a_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_p_a_bk")))    return Gamma_a_bk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_p_sjk")))  return Gaussian_sjk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_p_sk")))   return Gaussian_sk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_p_sj")))   return Gaussian_sj_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_p_s")))    return Gaussian_s_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_p_sjsk"))) return Gaussian_sjsk_;
  if (toUpperString(type) == toUpperString(_T("Categorical_p_pjk"))) return Categorical_pjk_;
  if (toUpperString(type) == toUpperString(_T("Categorical_p_pk")))  return Categorical_pk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_p_ljk")))  return Poisson_ljk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_p_lk")))   return Poisson_lk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_p_ljlk"))) return Poisson_ljlk_;
  if (toUpperString(type) == toUpperString(_T("Kmm_p_sk")))       return Kmm_sk_;
  if (toUpperString(type) == toUpperString(_T("Kmm_p_s")))        return Kmm_s_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBkQkDk"))) return HDGaussian_AjkBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBkQkD")))  return HDGaussian_AjkBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBkQDk")))  return HDGaussian_AjkBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBkQD")))   return HDGaussian_AjkBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBQkDk")))  return HDGaussian_AjkBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBQkD")))   return HDGaussian_AjkBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBQDk")))   return HDGaussian_AjkBQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjkBQD")))    return HDGaussian_AjkBQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBkQkDk")))  return HDGaussian_AkBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBkQkD")))   return HDGaussian_AkBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBkQDk")))   return HDGaussian_AkBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBkQD")))    return HDGaussian_AkBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBQkDk")))   return HDGaussian_AkBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBQkD")))    return HDGaussian_AkBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBQDk")))    return HDGaussian_AkBQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AkBQD")))     return HDGaussian_AkBQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjBkQkDk")))  return HDGaussian_AjBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjBkQkD")))   return HDGaussian_AjBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjBkQDk")))   return HDGaussian_AjBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjBkQD")))    return HDGaussian_AjBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjBQkDk")))   return HDGaussian_AjBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_AjBQkD")))    return HDGaussian_AjBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_ABkQkDk")))   return HDGaussian_ABkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_ABkQkD")))    return HDGaussian_ABkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_ABkQDk")))    return HDGaussian_ABkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_ABkQD")))     return HDGaussian_ABkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_ABQkDk")))    return HDGaussian_ABQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_ABQkD")))     return HDGaussian_ABQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_p_ABQD")))      return HDGaussian_ABQD_;
  freeProp = true;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ajk_bjk"))) return Gamma_ajk_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ajk_bk")))  return Gamma_ajk_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ajk_bj")))  return Gamma_ajk_bj_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ajk_b")))   return Gamma_ajk_b_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ak_bjk")))  return Gamma_ak_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ak_bk")))   return Gamma_ak_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ak_bj")))   return Gamma_ak_bj_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_ak_b")))    return Gamma_ak_b_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_aj_bjk")))  return Gamma_aj_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_aj_bk")))   return Gamma_aj_bk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_a_bjk")))   return Gamma_a_bjk_;
  if (toUpperString(type) == toUpperString(_T("Gamma_pk_a_bk")))    return Gamma_a_bk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_pk_sjk")))  return Gaussian_sjk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_pk_sk")))   return Gaussian_sk_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_pk_sj")))   return Gaussian_sj_;
  if (toUpperString(type) == toUpperString(_T("Gaussian_pk_s")))    return Gaussian_s_;
  if (toUpperString(type) == toUpperString(_T("Categorical_pk_pjk"))) return Categorical_pjk_;
  if (toUpperString(type) == toUpperString(_T("Categorical_pk_pk")))  return Categorical_pk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_pk_ljk")))   return Poisson_ljk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_pk_lk")))    return Poisson_lk_;
  if (toUpperString(type) == toUpperString(_T("Poisson_pk_ljlk")))  return Poisson_ljlk_;
  if (toUpperString(type) == toUpperString(_T("Kmm_pk_sk")))        return Kmm_sk_;
  if (toUpperString(type) == toUpperString(_T("Kmm_pk_s")))         return Kmm_s_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBkQkDk"))) return HDGaussian_AjkBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBkQkD")))  return HDGaussian_AjkBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBkQDk")))  return HDGaussian_AjkBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBkQD")))   return HDGaussian_AjkBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBQkDk")))  return HDGaussian_AjkBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBQkD")))   return HDGaussian_AjkBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBQDk")))   return HDGaussian_AjkBQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjkBQD")))    return HDGaussian_AjkBQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBkQkDk")))  return HDGaussian_AkBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBkQkD")))   return HDGaussian_AkBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBkQDk")))   return HDGaussian_AkBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBkQD")))    return HDGaussian_AkBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBQkDk")))   return HDGaussian_AkBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBQkD")))    return HDGaussian_AkBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBQDk")))    return HDGaussian_AkBQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AkBQD")))     return HDGaussian_AkBQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjBkQkDk")))  return HDGaussian_AjBkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjBkQkD")))   return HDGaussian_AjBkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjBkQDk")))   return HDGaussian_AjBkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjBkQD")))    return HDGaussian_AjBkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjBQkDk")))   return HDGaussian_AjBQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_AjBQkD")))    return HDGaussian_AjBQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_ABkQkDk")))   return HDGaussian_ABkQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_ABkQkD")))    return HDGaussian_ABkQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_ABkQDk")))    return HDGaussian_ABkQDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_ABkQD")))     return HDGaussian_ABkQD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_ABQkDk")))    return HDGaussian_ABQkDk_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_ABQkD")))     return HDGaussian_ABQkD_;
  if (toUpperString(type) == toUpperString(_T("HDGaussian_pk_ABQD")))      return HDGaussian_ABQD_;
#ifdef STK_MIXTURE_DEBUG
  stk_cout << _T("In stringToMixture, mixture ") << type << _T(" not found.\n");
#endif
  return unknown_mixture_;
}

References _T, STK::Clust::Categorical_pjk_, STK::Clust::Categorical_pk_, STK::Clust::Gamma_a_bjk_, STK::Clust::Gamma_a_bk_, STK::Clust::Gamma_aj_bjk_, STK::Clust::Gamma_aj_bk_, STK::Clust::Gamma_ajk_b_, STK::Clust::Gamma_ajk_bj_, STK::Clust::Gamma_ajk_bjk_, STK::Clust::Gamma_ajk_bk_, STK::Clust::Gamma_ak_b_, STK::Clust::Gamma_ak_bj_, STK::Clust::Gamma_ak_bjk_, STK::Clust::Gamma_ak_bk_, STK::Clust::Gaussian_s_, STK::Clust::Gaussian_sj_, STK::Clust::Gaussian_sjk_, STK::Clust::Gaussian_sjsk_, STK::Clust::Gaussian_sk_, STK::Clust::HDGaussian_ABkQD_, STK::Clust::HDGaussian_ABkQDk_, STK::Clust::HDGaussian_ABkQkD_, STK::Clust::HDGaussian_ABkQkDk_, STK::Clust::HDGaussian_ABQD_, STK::Clust::HDGaussian_ABQkD_, STK::Clust::HDGaussian_ABQkDk_, STK::Clust::HDGaussian_AjBkQD_, STK::Clust::HDGaussian_AjBkQDk_, STK::Clust::HDGaussian_AjBkQkD_, STK::Clust::HDGaussian_AjBkQkDk_, STK::Clust::HDGaussian_AjBQkD_, STK::Clust::HDGaussian_AjBQkDk_, STK::Clust::HDGaussian_AjkBkQD_, STK::Clust::HDGaussian_AjkBkQDk_, STK::Clust::HDGaussian_AjkBkQkD_, STK::Clust::HDGaussian_AjkBkQkDk_, STK::Clust::HDGaussian_AjkBQD_, STK::Clust::HDGaussian_AjkBQDk_, STK::Clust::HDGaussian_AjkBQkD_, STK::Clust::HDGaussian_AjkBQkDk_, STK::Clust::HDGaussian_AkBkQD_, STK::Clust::HDGaussian_AkBkQDk_, STK::Clust::HDGaussian_AkBkQkD_, STK::Clust::HDGaussian_AkBkQkDk_, STK::Clust::HDGaussian_AkBQD_, STK::Clust::HDGaussian_AkBQDk_, STK::Clust::HDGaussian_AkBQkD_, STK::Clust::HDGaussian_AkBQkDk_, STK::Clust::Kmm_s_, STK::Clust::Kmm_sk_, STK::Clust::Poisson_ljk_, STK::Clust::Poisson_ljlk_, STK::Clust::Poisson_lk_, stk_cout, STK::toUpperString(), and STK::Clust::unknown_mixture_.

stringToPredictAlgo()

algoPredictType STK::Clust::stringToPredictAlgo

(

String const &

type

)

Convert a String to an algoPredictType.

The recognized strings are

Algorithm
"em"
"semiSem"

Parameters

type	the type of algorithm wanted

Returns

the algoPredictType corresponding (default is em)

Note

The capitalized letters have no effect and if the string is not found in the list above, the type Clust::emPredictAlgo_ is returned.

Definition at line 118 of file STK_Clust_Util.cpp.

{
  if (toUpperString(type) == toUpperString(_T("em"))) return emPredictAlgo_;
  if (toUpperString(type) == toUpperString(_T("semiSem"))) return semiSEMPredictAlgo_;
  return emPredictAlgo_;
}

References _T, STK::Clust::emPredictAlgo_, STK::Clust::semiSEMPredictAlgo_, and STK::toUpperString().

Variable Documentation

defaultAlgoInInit

const Clust::algoType STK::Clust::defaultAlgoInInit = emAlgo_

Default algorithm type in initialization.

Definition at line 857 of file STK_Clust_Util.h.

defaultAlgoLongRun

const Clust::algoType STK::Clust::defaultAlgoLongRun = emAlgo_

Default algorithm type in long run.

Definition at line 877 of file STK_Clust_Util.h.

defaultAlgoShortRun

const Clust::algoType STK::Clust::defaultAlgoShortRun = emAlgo_

Default algorithm type in short run.

Definition at line 867 of file STK_Clust_Util.h.

defaultEpsilonInInit

const Real STK::Clust::defaultEpsilonInInit = 1e-02

Default epsilon in the short runs (used in strategy)

Definition at line 863 of file STK_Clust_Util.h.

defaultEpsilonLongRun

const Real STK::Clust::defaultEpsilonLongRun = 1e-08

Default epsilon in the long run (used in strategy)

Definition at line 883 of file STK_Clust_Util.h.

defaultEpsilonShortRun

const Real STK::Clust::defaultEpsilonShortRun = 1e-04

Default epsilon in the short runs (used in strategy)

Definition at line 873 of file STK_Clust_Util.h.

defaultInitType

const Clust::initType STK::Clust::defaultInitType = randomFuzzyInit_

Default algorithm type in short run.

Definition at line 851 of file STK_Clust_Util.h.

defaultMaxIterLongRun

const int STK::Clust::defaultMaxIterLongRun = 1000

Default number of iterations in the long run (used in FullStrategy)

Definition at line 880 of file STK_Clust_Util.h.

defaultMaxIterShortRun

const int STK::Clust::defaultMaxIterShortRun = 200

Default number of iterations in the short runs (used in FullStrategy)

Definition at line 870 of file STK_Clust_Util.h.

defaultNbInit

const int STK::Clust::defaultNbInit = 5

Default number of initializations to perform.

Definition at line 854 of file STK_Clust_Util.h.

defaultNbIterMaxInInit

const int STK::Clust::defaultNbIterMaxInInit = 20

Default number of iteration in an initialization algorithm.

Definition at line 860 of file STK_Clust_Util.h.

defaultNbTry

const int STK::Clust::defaultNbTry = 5

Default number of try in an estimation strategy.

Definition at line 847 of file STK_Clust_Util.h.