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## Package de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures

Provides the facilities to learn the structure of a `BayesianNetworkScoringFunction`.

See:
Description

Class Summary
InhomogeneousMarkov | Class for a network structure of a `BayesianNetworkScoringFunction` 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.

## Package de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures Description

Provides the facilities to learn the structure of a `BayesianNetworkScoringFunction`. 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`

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