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## Uses of Class
de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

Packages that use AbstractNormalizableScoringFunction
de.jstacs.scoringFunctions | Provides `ScoringFunction`s that can be used in a `ScoreClassifier`.
de.jstacs.scoringFunctions.directedGraphicalModels | Provides `ScoringFunction`s that are equivalent to directed graphical models.
de.jstacs.scoringFunctions.homogeneous | Provides `ScoringFunction`s that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence
de.jstacs.scoringFunctions.mix | Provides `ScoringFunction`s that are mixtures of other `ScoringFunction`s.

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions
`class` | `IndependentProductScoringFunction` This class enables the user to model parts of the sequence independent of each other.
`class` | `MRFScoringFunction` This class implements the scoring function for any MRF.
`class` | `UniformScoringFunction` This scoring function does nothing.
`class` | `VariableLengthScoringFunction` This is the main class for all ScoringFunctions that allow to score subsequences of arbitrary length.

Methods in de.jstacs.scoringFunctions that return AbstractNormalizableScoringFunction
`AbstractNormalizableScoringFunction` | `AbstractNormalizableScoringFunction.clone()`

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels
`class` | `BayesianNetworkScoringFunction` This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.homogeneous

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.homogeneous
`class` | `HMM0ScoringFunction` This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
`class` | `HMMScoringFunction` This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.
`class` | `HomogeneousScoringFunction` This is the main class for all homogeneous ScoringFunctions.
`class` | `UniformHomogeneousScoringFunction` This scoring function does nothing.

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix
`class` | `AbstractMixtureScoringFunction` This main abstract class for any mixture (e.g.
`class` | `MixtureScoringFunction` This class implements a real mixture model.

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