Uses of Package
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

Packages that use de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

de.jstacs.sequenceScores.statisticalModels.trainable	Provides all TrainableStatisticalModels, which can be learned from a single DataSet.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous	This package contains various inhomogeneous models.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous used by de.jstacs.sequenceScores.statisticalModels.trainable

BayesianNetworkTrainSM
The class implements a Bayesian network ( StructureLearner.ModelType.BN ) of fixed order.

FSDAGTrainSM
This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGTrainSM).

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete

InhCondProb
This class handles (conditional) probabilities of sequences for inhomogeneous models.

MEMConstraint
This constraint can be used for any maximum entropy model (MEM) application.

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

BayesianNetworkTrainSM
The class implements a Bayesian network ( StructureLearner.ModelType.BN ) of fixed order.

DAGTrainSM
The abstract class for directed acyclic graphical models (DAGTrainSM).

FSDAGModelForGibbsSampling
This is the class for a fixed structure directed acyclic graphical model (see FSDAGTrainSM) that can be used in a Gibbs sampling.

FSDAGTrainSM
This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGTrainSM).

InhCondProb
This class handles (conditional) probabilities of sequences for inhomogeneous models.

InhConstraint
This class is the superclass for all inhomogeneous constraints.

InhomogeneousDGTrainSM
This class is the main class for all inhomogeneous discrete graphical models (InhomogeneousDGTrainSM).

MEMConstraint
This constraint can be used for any maximum entropy model (MEM) application.

SequenceIterator
This class is used to iterate over a discrete sequence.

StructureLearner.LearningType
This enum defines the different types of learning that are possible with the StructureLearner.

StructureLearner.ModelType
This enum defines the different types of models that can be learned with the StructureLearner.

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters

FSDAGTrainSM
This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGTrainSM).

InhomogeneousDGTrainSM
This class is the main class for all inhomogeneous discrete graphical models (InhomogeneousDGTrainSM).

StructureLearner.LearningType
This enum defines the different types of learning that are possible with the StructureLearner.

StructureLearner.ModelType
This enum defines the different types of models that can be learned with the StructureLearner.

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared

FSDAGTrainSM
This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGTrainSM).

StructureLearner.LearningType
This enum defines the different types of learning that are possible with the StructureLearner.

StructureLearner.ModelType
This enum defines the different types of models that can be learned with the StructureLearner.