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

Packages that use ScoringFunction
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.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 ScoringFunction in de.jstacs.classifier.scoringFunctionBased

Fields in de.jstacs.classifier.scoringFunctionBased declared as ScoringFunction
`protected ScoringFunction[]` | `ScoreClassifier.score` The internally used scoring functions.

Methods in de.jstacs.classifier.scoringFunctionBased that return ScoringFunction
`ScoringFunction` | `ScoreClassifier.getScoringFunction(int i)` Returns the internally used ScoringFunction with index `i`.
`ScoringFunction[]` | `ScoreClassifier.getScoringFunctions()` Returns all internally used ScoringFunctions in the internal order.

Methods in de.jstacs.classifier.scoringFunctionBased with parameters of type ScoringFunction
`abstract void` | `OptimizableFunction.reset(ScoringFunction[] score)` Resets the scoringFunctions and all precomputed values.

Constructors in de.jstacs.classifier.scoringFunctionBased with parameters of type ScoringFunction
`ScoreClassifier(ScoreClassifierParameterSet params, ScoringFunction... score)` The default constructor.

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

Methods in de.jstacs.classifier.scoringFunctionBased.cll with parameters of type ScoringFunction
`static CLLClassifier[]` | `CLLClassifier.create(CLLClassifierParameterSet params, LogPrior prior, ScoringFunction[]... functions)` This method creates an array of CLLClassifier by using the cross-product of the given ScoringFunctions.
`void` | `NormConditionalLogLikelihood.reset(ScoringFunction[] funs)`

Constructors in de.jstacs.classifier.scoringFunctionBased.cll with parameters of type ScoringFunction
`CLLClassifier(CLLClassifierParameterSet params, LogPrior prior, ScoringFunction... score)` The default constructor.
`CLLClassifier(CLLClassifierParameterSet params, ScoringFunction... score)` The default constructor.
`NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, boolean norm, boolean freeParams)` The constructor creates an instance of the log conditional likelihood.
`NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, LogPrior prior, boolean norm, boolean freeParams)` The constructor creates an instance using the given prior.

Uses of ScoringFunction in de.jstacs.classifier.scoringFunctionBased.logPrior

Methods in de.jstacs.classifier.scoringFunctionBased.logPrior with parameters of type ScoringFunction
`void` | `SeparateLogPrior.set(boolean freeParameters, ScoringFunction... funs)`
`void` | `LogPrior.set(boolean freeParameters, ScoringFunction... funs)` Resets all pre-computed values to their initial values using the `ScoringFunction`s `funs`

Uses of ScoringFunction in de.jstacs.scoringFunctions

Subinterfaces of ScoringFunction in de.jstacs.scoringFunctions
`interface` | `NormalizableScoringFunction` The interface for normalizable ScoringFunctions.

Classes in de.jstacs.scoringFunctions that implement ScoringFunction
`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 that return ScoringFunction
`ScoringFunction` | `ScoringFunction.clone()` Creates a clone (deep copy) of the current `ScoringFunction` instance.

Uses of ScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels

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

Uses of ScoringFunction in de.jstacs.scoringFunctions.homogeneous

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

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

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