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## Uses of Interface
de.jstacs.scoringFunctions.NormalizableScoringFunction

Packages that use NormalizableScoringFunction
de.jstacs.classifier.scoringFunctionBased.logPrior | Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors
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 NormalizableScoringFunction in de.jstacs.classifier.scoringFunctionBased.logPrior

Fields in de.jstacs.classifier.scoringFunctionBased.logPrior declared as NormalizableScoringFunction
`protected NormalizableScoringFunction[]` | `SeparateLogPrior.funs` The `ScoringFunction`s using the parameters that shall be penalized

Uses of NormalizableScoringFunction in de.jstacs.scoringFunctions

Classes in de.jstacs.scoringFunctions that implement NormalizableScoringFunction
`class` | `AbstractNormalizableScoringFunction` This class is the main part of any ScoreClassifier.
`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 with parameters of type NormalizableScoringFunction
`static boolean` | `AbstractNormalizableScoringFunction.isNormalized(NormalizableScoringFunction... function)` This method checks whether all given NormalizableScoringFunctions are normalized.

Constructors in de.jstacs.scoringFunctions with parameters of type NormalizableScoringFunction
`IndependentProductScoringFunction(NormalizableScoringFunction... functions)` This constructor creates an instance of a given series of independent NormalizableScoringFunctions.
`IndependentProductScoringFunction(NormalizableScoringFunction[] functions, int[] length)` This constructor creates an instance of a given series of independent NormalizableScoringFunctions and lengths.

Uses of NormalizableScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels

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

Uses of NormalizableScoringFunction in de.jstacs.scoringFunctions.homogeneous

Classes in de.jstacs.scoringFunctions.homogeneous that implement NormalizableScoringFunction
`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 NormalizableScoringFunction in de.jstacs.scoringFunctions.mix

Classes in de.jstacs.scoringFunctions.mix that implement NormalizableScoringFunction
`class` | `AbstractMixtureScoringFunction` This main abstract class for any mixture (e.g.
`class` | `MixtureScoringFunction` This class implements a real mixture model.

Fields in de.jstacs.scoringFunctions.mix declared as NormalizableScoringFunction
`protected NormalizableScoringFunction[]` | `AbstractMixtureScoringFunction.function` This array contains the internal functions that are used to determine the score.

Methods in de.jstacs.scoringFunctions.mix that return NormalizableScoringFunction
`NormalizableScoringFunction` | `AbstractMixtureScoringFunction.getFunction(int index)` This method returns a specific internal function
`NormalizableScoringFunction[]` | `AbstractMixtureScoringFunction.getFunctions()` This method returns an array of clones of the internal used functions.
`NormalizableScoringFunction[]` | `AbstractMixtureScoringFunction.getScoringFunctions()` Returns a deep copy of all internal used ScoringFunctions

Methods in de.jstacs.scoringFunctions.mix with parameters of type NormalizableScoringFunction
`protected void` | `AbstractMixtureScoringFunction.cloneFunctions(NormalizableScoringFunction[] originalFunctions)` This method clones the given array of function and enables the user to do some postprocessing.

Constructors in de.jstacs.scoringFunctions.mix with parameters of type NormalizableScoringFunction
`AbstractMixtureScoringFunction(int length, int starts, int dimension, boolean optimizeHidden, boolean plugIn, NormalizableScoringFunction... function)` This constructor creates an AbstractMixtureScoringFunction.
`MixtureScoringFunction(int starts, boolean plugIn, NormalizableScoringFunction... component)` This constructor creates a mixture.

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