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

Provides the facilities to learn the structure of a BayesianNetworkDiffSM.

See:
Description

Class Summary

InhomogeneousMarkov	Class for a network structure of a BayesianNetworkDiffSM that is an inhomogeneous Markov model.
InhomogeneousMarkov.InhomogeneousMarkovParameterSet	Class for an InstanceParameterSet that defines the parameters of an InhomogeneousMarkov structure Measure.
Measure	Class for structure measures that derive an optimal structure with respect to some criterion within a class of possible structures from data.
Measure.MeasureParameterSet	This class is the super class of any ParameterSet that can be used to instantiate a Measure.

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

Provides the facilities to learn the structure of a BayesianNetworkDiffSM. The base is the Measure interface. Implementations of the interface can be found in the sub-packages. An implementation of an inhomogeneous Markov model, which does not require "real" structure learning, is provided with the class InhomogeneousMarkov.

See Also:

de.jstacs.parameters