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## Uses of Class
de.jstacs.classifier.scoringFunctionBased.OptimizableFunction.KindOfParameter

Packages that use OptimizableFunction.KindOfParameter
de.jstacs.classifier.scoringFunctionBased | Provides the classes for `Classifier`s that are based on `ScoringFunction`s.
de.jstacs.classifier.scoringFunctionBased.gendismix | Provides an implementation of a classifier that allows to train the parameters of a set of `NormalizableScoringFunction`s by a unified generative-discriminative learning principle
de.jstacs.motifDiscovery | This package provides the framework including the interface for any de novo motif discoverer

Uses of OptimizableFunction.KindOfParameter in de.jstacs.classifier.scoringFunctionBased

Methods in de.jstacs.classifier.scoringFunctionBased that return OptimizableFunction.KindOfParameter
`static OptimizableFunction.KindOfParameter` | `OptimizableFunction.KindOfParameter.valueOf(String name)` Returns the enum constant of this type with the specified name.
`static OptimizableFunction.KindOfParameter[]` | `OptimizableFunction.KindOfParameter.values()` Returns an array containing the constants of this enum type, in the order they are declared.

Methods in de.jstacs.classifier.scoringFunctionBased with parameters of type OptimizableFunction.KindOfParameter
`abstract double[]` | `OptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind)` Returns some parameters that can be used for instance as start parameters.
`double[]` | `AbstractOptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind)`
`void` | `SFBasedOptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind, double[] erg)`
`abstract void` | `AbstractOptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind, double[] erg)` This method enables the user to get the parameters without creating a new array.

Constructors in de.jstacs.classifier.scoringFunctionBased with parameters of type OptimizableFunction.KindOfParameter
`ScoreClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind)` The constructor for a simple, instantiated parameter set.

Uses of OptimizableFunction.KindOfParameter in de.jstacs.classifier.scoringFunctionBased.gendismix

Constructors in de.jstacs.classifier.scoringFunctionBased.gendismix with parameters of type OptimizableFunction.KindOfParameter
`GenDisMixClassifierParameterSet(AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind, boolean norm, int threads)` The default constructor that constructs a new `GenDisMixClassifierParameterSet`.
`GenDisMixClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind, boolean norm, int threads)` The default constructor that constructs a new `GenDisMixClassifierParameterSet`.

Uses of OptimizableFunction.KindOfParameter in de.jstacs.motifDiscovery

Methods in de.jstacs.motifDiscovery with parameters of type OptimizableFunction.KindOfParameter
`static double[][]` | `MutableMotifDiscovererToolbox.optimize(ScoringFunction[] funs, SFBasedOptimizableFunction opt, byte algorithm, double eps, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, boolean breakOnChanged, History[][] hist, int[][] minimalNewLength, OptimizableFunction.KindOfParameter plugIn, boolean maxPos)` This method tries to optimize the problem at hand as good as possible.
`static double[][]` | `MutableMotifDiscovererToolbox.optimize(ScoringFunction[] funs, SFBasedOptimizableFunction opt, byte algorithm, double eps, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, boolean breakOnChanged, History template, OptimizableFunction.KindOfParameter plugIn, boolean maxPos)` This method tries to optimize the problem at hand as good as possible.

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