Uses of Class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction

Packages that use AbstractMultiThreadedOptimizableFunction
Package	Description
de.jstacs.classifiers.differentiableSequenceScoreBased	Provides the classes for `Classifier`s that are based on `SequenceScore`s. It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior.
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.

Subclasses of AbstractMultiThreadedOptimizableFunction in de.jstacs.classifiers.differentiableSequenceScoreBased
Modifier and Type	Class and Description
`class`	`DiffSSBasedOptimizableFunction` This abstract class is the basis of all multi-threaded `OptimizableFunction`s that are based on `DifferentiableSequenceScore`s.

Subclasses of AbstractMultiThreadedOptimizableFunction in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix
Modifier and Type	Class and Description
`class`	`LogGenDisMixFunction` This class implements the the following function $\[f(\underline{\lambda}\|C,D,\underline{\alpha},\underline{\beta})$ The weights $\beta_i$ have to sum to 1.
`class`	`OneDataSetLogGenDisMixFunction` This class implements the the following function $\[f(\underline{\lambda}\|C,D,\underline{w},\underline{\alpha},\underline{\beta})$ where $w_{c,n}$ is the weight for sequence and class .

Uses of Classde.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction