Uses of Class
de.jstacs.models.AbstractModel

Packages that use AbstractModel

de.jstacs.models	Provides the interface Model and its abstract implementation AbstractModel, which is the super class of all other models.
de.jstacs.models.discrete
de.jstacs.models.discrete.homogeneous
de.jstacs.models.discrete.inhomogeneous	This package contains various inhomogeneous models.
de.jstacs.models.discrete.inhomogeneous.shared
de.jstacs.models.mixture	This package is the super package for any mixture model.
de.jstacs.models.mixture.motif

Uses of AbstractModel in de.jstacs.models

Subclasses of AbstractModel in de.jstacs.models

class	CompositeModel This class is for modelling sequences by modelling the different positions of the each sequence by different models.
class	NormalizableScoringFunctionModel This model can be used to use a NormalizableScoringFunction as model.
class	UniformModel This class represents a uniform model.
class	VariableLengthWrapperModel This class allows to train any Model on Samples of Sequences with variable length if each individual length is at least Model.getLength().

Methods in de.jstacs.models that return AbstractModel

AbstractModel

AbstractModel.clone() Follows the conventions of Object's clone()-method.

Uses of AbstractModel in de.jstacs.models.discrete

Subclasses of AbstractModel in de.jstacs.models.discrete

class

DiscreteGraphicalModel This is the main class for all discrete graphical models (DGM).

Uses of AbstractModel in de.jstacs.models.discrete.homogeneous

Subclasses of AbstractModel in de.jstacs.models.discrete.homogeneous

class	HomogeneousMM This class implements homogeneous Markov models (hMM) of arbitrary order.
class	HomogeneousModel This class implements homogeneous models of arbitrary order.

Uses of AbstractModel in de.jstacs.models.discrete.inhomogeneous

Subclasses of AbstractModel in de.jstacs.models.discrete.inhomogeneous

class	BayesianNetworkModel The class implements a Bayesian network ( StructureLearner.ModelType.BN ) of fixed order.
class	DAGModel The abstract class for directed acyclic graphical models (DAGModel).
class	FSDAGModel This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGModel).
class	FSDAGModelForGibbsSampling This is the class for a fixed structure directed acyclic graphical model (see FSDAGModel) that can be used in a Gibbs sampling.
class	InhomogeneousDGM This class is the main class for all inhomogeneous discrete graphical models (InhomogeneousDGM).

Uses of AbstractModel in de.jstacs.models.discrete.inhomogeneous.shared

Subclasses of AbstractModel in de.jstacs.models.discrete.inhomogeneous.shared

class

SharedStructureMixture This class handles a mixture of models with the same structure that is learned via EM.

Uses of AbstractModel in de.jstacs.models.mixture

Subclasses of AbstractModel in de.jstacs.models.mixture

class	AbstractMixtureModel This is the abstract class for all kinds of mixture models.
class	MixtureModel The class for a mixture model of any Models.
class	StrandModel This model handles sequences that can either lie on the forward strand or on the reverse complementary strand.

Uses of AbstractModel in de.jstacs.models.mixture.motif

Subclasses of AbstractModel in de.jstacs.models.mixture.motif

class	HiddenMotifMixture This is the main class that every generative motif discoverer should implement.
class	SingleHiddenMotifMixture This class enables the user to search for a single motif in a sequence.