Uses of Class de.jstacs.classifier.scoringFunctionBased.sampling.SamplingScoreBasedClassifierParameterSet

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Uses of Class
de.jstacs.classifier.scoringFunctionBased.sampling.SamplingScoreBasedClassifierParameterSet

Packages that use SamplingScoreBasedClassifierParameterSet
de.jstacs.classifier.scoringFunctionBased.sampling	Provides the classes for `AbstractScoreBasedClassifier`s that are based on `SamplingScoringFunction`s and that sample parameters using the Metropolis-Hastings algorithm.

Uses of SamplingScoreBasedClassifierParameterSet in de.jstacs.classifier.scoringFunctionBased.sampling

Subclasses of SamplingScoreBasedClassifierParameterSet in de.jstacs.classifier.scoringFunctionBased.sampling
`class`	`SamplingGenDisMixClassifierParameterSet` `ParameterSet` to instantiate a `SamplingGenDisMixClassifier`.

Fields in de.jstacs.classifier.scoringFunctionBased.sampling declared as SamplingScoreBasedClassifierParameterSet
`protected SamplingScoreBasedClassifierParameterSet`	`SamplingScoreBasedClassifier.params` Parameters

Methods in de.jstacs.classifier.scoringFunctionBased.sampling that return SamplingScoreBasedClassifierParameterSet
`SamplingScoreBasedClassifierParameterSet`	`SamplingScoreBasedClassifierParameterSet.clone()`

Constructors in de.jstacs.classifier.scoringFunctionBased.sampling with parameters of type SamplingScoreBasedClassifierParameterSet
`SamplingScoreBasedClassifier(SamplingScoreBasedClassifierParameterSet params, BurnInTest burnInTest, double[] classVariances, SamplingScoringFunction... scoringFunctions)` Creates a new `SamplingScoreBasedClassifier` using the parameters in `params`, a specified `BurnInTest` (or `null` for no burn-in test), a set of sampling variances, which may be different for each of the classes (in analogy to equivalent sample size for the Dirichlet distribution), and set set of `SamplingScoringFunction`s for each of the classes.

Constructors in de.jstacs.classifier.scoringFunctionBased.sampling with parameters of type SamplingScoreBasedClassifierParameterSet

SamplingScoreBasedClassifier(SamplingScoreBasedClassifierParameterSet params,
                             BurnInTest burnInTest,
                             double[] classVariances,
                             SamplingScoringFunction... scoringFunctions)

Creates a new SamplingScoreBasedClassifier using the parameters in params, a specified BurnInTest (or null for no burn-in test), a set of sampling variances, which may be different for each of the classes (in analogy to equivalent sample size for the Dirichlet distribution), and set set of SamplingScoringFunctions for each of the classes.