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## Uses of Class
de.jstacs.parameters.SequenceScoringParameterSet

Packages that use SequenceScoringParameterSet
de.jstacs.classifier.scoringFunctionBased | Provides the classes for `Classifier`s that are based on `ScoringFunction`s.
de.jstacs.classifier.scoringFunctionBased.cll | Provides the implementation of the log conditional likelihood as an `OptimizableFunction` and a classifier that uses log conditional likelihood or supervised posterior to learn the parameters of a set of `ScoringFunctions`
de.jstacs.models.discrete |
de.jstacs.models.discrete.homogeneous.parameters |
de.jstacs.models.discrete.inhomogeneous.parameters |
de.jstacs.models.mixture.gibbssampling | This package contains many classes that can be used while a Gibbs sampling.
de.jstacs.parameters | This package provides classes for parameters that establish a general convention for the description of parameters as defined in the `Parameter`-interface.
de.jstacs.scoringFunctions.directedGraphicalModels | Provides `ScoringFunction`s that are equivalent to directed graphical models.

Uses of SequenceScoringParameterSet in de.jstacs.classifier.scoringFunctionBased

Subclasses of SequenceScoringParameterSet in de.jstacs.classifier.scoringFunctionBased
`class` | `ScoreClassifierParameterSet` A set of `Parameter`s for any `ScoreClassifier`.

Uses of SequenceScoringParameterSet in de.jstacs.classifier.scoringFunctionBased.cll

Subclasses of SequenceScoringParameterSet in de.jstacs.classifier.scoringFunctionBased.cll
`class` | `CLLClassifierParameterSet` This class contains the parameters for the `CLLClassifier`.

Uses of SequenceScoringParameterSet in de.jstacs.models.discrete

Subclasses of SequenceScoringParameterSet in de.jstacs.models.discrete
`class` | `DGMParameterSet` The super `ParameterSet` for any parameter set of a `DiscreteGraphicalModel`.

Uses of SequenceScoringParameterSet in de.jstacs.models.discrete.homogeneous.parameters

Subclasses of SequenceScoringParameterSet in de.jstacs.models.discrete.homogeneous.parameters
`class` | `HomMMParameterSet` This class implements a container for all parameters of a homogeneous Markov model.
`class` | `HomogeneousModelParameterSet` This class implements a container for all parameters of any homogeneous model.

Uses of SequenceScoringParameterSet in de.jstacs.models.discrete.inhomogeneous.parameters

Subclasses of SequenceScoringParameterSet in de.jstacs.models.discrete.inhomogeneous.parameters
`class` | `BayesianNetworkModelParameterSet` The `ParameterSet` for the class `BayesianNetworkModel`.
`class` | `FSDAGMParameterSet` The class for the parameters of a `FSDAGModel` (fixed structure directed acyclic graphical model).
`class` | `IDGMParameterSet` This is the abstract container of parameters that is a root container for all inhomogeneous discrete graphical model parameter containers.

Uses of SequenceScoringParameterSet in de.jstacs.models.mixture.gibbssampling

Subclasses of SequenceScoringParameterSet in de.jstacs.models.mixture.gibbssampling
`class` | `FSDAGModelForGibbsSamplingParameterSet` The class for the parameters of a `FSDAGModelForGibbsSampling`.

Uses of SequenceScoringParameterSet in de.jstacs.parameters

Methods in de.jstacs.parameters that return SequenceScoringParameterSet
`SequenceScoringParameterSet` | `SequenceScoringParameterSet.clone()`

Uses of SequenceScoringParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels

Subclasses of SequenceScoringParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels
`class` | `BayesianNetworkScoringFunctionParameterSet` Class for the parameters of a `BayesianNetworkScoringFunction`.

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