Uses of Class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple

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Uses of Class
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple

Packages that use LearningPrinciple
de.jstacs.classifiers	This package provides the framework for any classifier.
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix	Provides an implementation of a classifier that allows to train the parameters of a set of `DifferentiableStatisticalModel`s by a unified generative-discriminative learning principle.
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling	Provides the classes for `AbstractScoreBasedClassifier`s that are based on `SamplingDifferentiableStatisticalModel`s and that sample parameters using the Metropolis-Hastings algorithm.

Uses of LearningPrinciple in de.jstacs.classifiers

Methods in de.jstacs.classifiers with parameters of type LearningPrinciple
`static AbstractClassifier`	`ClassifierFactory.createClassifier(LearningPrinciple principle, DifferentiableStatisticalModel... models)` Creates a classifier that is based on at least two `DifferentiableStatisticalModel`s.

Uses of LearningPrinciple in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix that return LearningPrinciple
`static LearningPrinciple`	`LearningPrinciple.valueOf(String name)` Returns the enum constant of this type with the specified name.
`static LearningPrinciple[]`	`LearningPrinciple.values()` Returns an array containing the constants of this enum type, in the order they are declared.

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix with parameters of type LearningPrinciple
`static double[]`	`LearningPrinciple.getBeta(LearningPrinciple key)` This method returns the standard weights for a predefined key.

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix with parameters of type LearningPrinciple
`GenDisMixClassifier(GenDisMixClassifierParameterSet params, LogPrior prior, LearningPrinciple key, DifferentiableStatisticalModel... score)` This convenience constructor creates an array of weights for an elementary learning principle and calls the main constructor.

Uses of LearningPrinciple in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling with parameters of type LearningPrinciple
`SamplingGenDisMixClassifier(SamplingGenDisMixClassifierParameterSet params, BurnInTest burnInTest, double[] classVariances, LogPrior prior, LearningPrinciple principle, SamplingDifferentiableStatisticalModel... scoringFunctions)` Creates a new `SamplingGenDisMixClassifier` using the external parameters `params`, a burn-in test, a set of sampling variances for the different classes, a prior on the parameters, a learning principle, and scoring functions that model the distribution for each of the classes.

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling with parameters of type LearningPrinciple

SamplingGenDisMixClassifier(SamplingGenDisMixClassifierParameterSet params,
                            BurnInTest burnInTest,
                            double[] classVariances,
                            LogPrior prior,
                            LearningPrinciple principle,
                            SamplingDifferentiableStatisticalModel... scoringFunctions)

Creates a new SamplingGenDisMixClassifier using the external parameters params, a burn-in test, a set of sampling variances for the different classes, a prior on the parameters, a learning principle, and scoring functions that model the distribution for each of the classes.