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

Packages that use OptimizableFunction
de.jstacs.classifier.scoringFunctionBased Provides the classes for Classifiers that are based on ScoringFunctions. 
de.jstacs.classifier.scoringFunctionBased.gendismix Provides an implementation of a classifier that allows to train the parameters of a set of NormalizableScoringFunctions by a unified generative-discriminative learning principle 
 

Uses of OptimizableFunction in de.jstacs.classifier.scoringFunctionBased
 

Subclasses of OptimizableFunction in de.jstacs.classifier.scoringFunctionBased
 class AbstractMultiThreadedOptimizableFunction
          This class enables the user to exploit all CPUs of an computer by using threads.
 class AbstractOptimizableFunction
          This class extends OptimizableFunction and implements some common methods.
 class SFBasedOptimizableFunction
          This abstract class is the basis of all multi-threaded OptimizableFunctions that are based on ScoringFunctions.
 

Methods in de.jstacs.classifier.scoringFunctionBased with parameters of type OptimizableFunction
protected  OptimizableFunction.KindOfParameter ScoreClassifier.preoptimize(OptimizableFunction f)
          This method allows to pre-optimize the parameter before the real optimization.
 

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

Subclasses of OptimizableFunction in de.jstacs.classifier.scoringFunctionBased.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 OneSampleLogGenDisMixFunction
          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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