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

Packages that use AbstractMultiThreadedOptimizableFunction
de.jstacs.classifiers.differentiableSequenceScoreBased Provides the classes for Classifiers that are based on SequenceScores.
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 DifferentiableStatisticalModels by a unified generative-discriminative learning principle. 
 

Uses of AbstractMultiThreadedOptimizableFunction in de.jstacs.classifiers.differentiableSequenceScoreBased
 

Subclasses of AbstractMultiThreadedOptimizableFunction in de.jstacs.classifiers.differentiableSequenceScoreBased
 class DiffSSBasedOptimizableFunction
          This abstract class is the basis of all multi-threaded OptimizableFunctions that are based on DifferentiableSequenceScores.
 

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

Subclasses of AbstractMultiThreadedOptimizableFunction in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix
 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 $d_n$ and class $c$.
 

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