Uses of Class
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

Packages that use DiscreteGraphicalTrainSM

Package	Description
de.jstacs.sequenceScores.statisticalModels.trainable.discrete
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous	This package contains various inhomogeneous models.

Uses of DiscreteGraphicalTrainSM in de.jstacs.sequenceScores.statisticalModels.trainable.discrete

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete with type parameters of type DiscreteGraphicalTrainSM

Modifier and Type	Class and Description
class	DGTrainSMParameterSet<T extends DiscreteGraphicalTrainSM> The super ParameterSet for any parameter set of a DiscreteGraphicalTrainSM.

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete that return DiscreteGraphicalTrainSM

Modifier and Type	Method and Description
DiscreteGraphicalTrainSM	DiscreteGraphicalTrainSM.clone()

Uses of DiscreteGraphicalTrainSM in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

Subclasses of DiscreteGraphicalTrainSM in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

Modifier and Type	Class and Description
class	HomogeneousMM This class implements homogeneous Markov models (hMM) of arbitrary order.
class	HomogeneousTrainSM This class implements homogeneous models of arbitrary order.

Uses of DiscreteGraphicalTrainSM in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

Subclasses of DiscreteGraphicalTrainSM in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

Modifier and Type	Class and Description
class	BayesianNetworkTrainSM The class implements a Bayesian network ( StructureLearner.ModelType.BN ) of fixed order.
class	DAGTrainSM The abstract class for directed acyclic graphical models (DAGTrainSM).
class	FSDAGModelForGibbsSampling This is the class for a fixed structure directed acyclic graphical model (see FSDAGTrainSM) that can be used in a Gibbs sampling.
class	FSDAGTrainSM This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGTrainSM).
class	FSMEManager This class can be used for any discrete fixed structure maximum entropy model (FSMEM).
class	InhomogeneousDGTrainSM This class is the main class for all inhomogeneous discrete graphical models (InhomogeneousDGTrainSM).
class	MEManager This class is the super class for all maximum entropy models