Package de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Provides DifferentiableStatisticalModels that are directed graphical models.

See:
Description

Class Summary

BayesianNetworkDiffSM	This class implements a scoring function that is a moral directed graphical model, i.e.
BayesianNetworkDiffSMParameterSet	Class for the parameters of a BayesianNetworkDiffSM.
BNDiffSMParameter	Class for the parameters of a BayesianNetworkDiffSM.
BNDiffSMParameterTree	Class for the tree that represents the context of a BNDiffSMParameter in a BayesianNetworkDiffSM.
MarkovModelDiffSM	This class implements a AbstractDifferentiableStatisticalModel for an inhomogeneous Markov model.

Package de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels Description

Provides DifferentiableStatisticalModels that are directed graphical models. The currently implemented BayesianNetworkDiffSM provides structure learning for inhomogeneous Markov models, Bayesian trees, and permuted Markov models, but can be extended to other graph structures easily using the Measure interface. It is important to define only moral Bayesian network structures because of the chosen parameterization.