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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.
de.jstacs.scoringFunctions.mix.motifSearch |

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions
`class` | `AbstractVariableLengthScoringFunction` This abstract class implements some methods declared in `NormalizableScoringFunction` based on the declaration of methods in `VariableLengthScoringFunction`.
`class` | `CMMScoringFunction` This scoring function implements a cyclic Markov model of arbitrary order and periodicity for any sequence length.
`class` | `IndependentProductScoringFunction` This class enables the user to model parts of a sequence independent of each other.
`class` | `MRFScoringFunction` This class implements the scoring function for any MRF (Markov Random Field).
`class` | `NormalizedScoringFunction` This class makes an unnormalized ScoringFunction to a normalized ScoringFunction.
`class` | `UniformScoringFunction` This `ScoringFunction` does nothing.

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.
`class` | `MutableMarkovModelScoringFunction` This class implements a `AbstractNormalizableScoringFunction` for an inhomogeneous Markov model.

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 `ScoringFunction`s.
`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 scoring function (e.g.
`class` | `MixtureScoringFunction` This class implements a real mixture model.
`class` | `StrandScoringFunction` This class enables the user to search on both strand.
`class` | `VariableLengthMixtureScoringFunction` This class implements a mixture of `VariableLengthScoringFunction` by extending `MixtureScoringFunction` and implementing the methods of `VariableLengthScoringFunction`.

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix.motifSearch

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix.motifSearch
`class` | `DurationScoringFunction` This class is the super class for all one dimensional position scoring functions that can be used as durations for semi Markov models.
`class` | `HiddenMotifsMixture` This class handles mixtures with at least one hidden motif.
`class` | `MixtureDuration` This class implements a mixture of `DurationScoringFunction`s.
`class` | `PositionScoringFunction` This class implements a position scoring function that enables the user to get a score without using a Sequence object.
`class` | `SkewNormalLikeScoringFunction` This class implements a skew normal like discrete truncated distribution.
`class` | `UniformDurationScoringFunction` This scoring function implements a uniform distribution for positions.

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