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

Provides the facilities to learn the structure of a `BayesianNetworkScoringFunction` as a Bayesian tree using a number of measures to define a rating of structures

See:
Description

Class Summary
BTExplainingAwayResidual | Structure learning `Measure` that computes a maximum spanning tree based on the explaining away residual and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a `BayesianNetworkScoringFunction` .
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet | Class for the parameters of a `BTExplainingAwayResidual` structure `Measure`.
BTMutualInformation | Structure learning `Measure` that computes a maximum spanning tree based on mutual information and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a `BayesianNetworkScoringFunction` .
BTMutualInformation.BTMutualInformationParameterSet | Class for the parameters of a `BTMutualInformation` structure `Measure`.

Enum Summary
BTMutualInformation.DataSource | `Enum` defining the possible sources of data to compute the mutual information.

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

Provides the facilities to learn the structure of a `BayesianNetworkScoringFunction` as a Bayesian tree using a number of measures to define a rating of structures.

See Also:
  `de.jstacs.parameters`

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