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Uses of Package
de.jstacs.classifier.scoringFunctionBased.gendismix

Packages that use de.jstacs.classifier.scoringFunctionBased.gendismix
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 
de.jstacs.classifier.scoringFunctionBased.msp Provides an implementation of a classifier that allows to train the parameters of a set of ScoringFunctions either by maximum supervised posterior (MSP) or by maximum conditional likelihood (MCL) 
de.jstacs.classifier.scoringFunctionBased.sampling Provides the classes for AbstractScoreBasedClassifiers that are based on SamplingScoringFunctions and that sample parameters using the Metropolis-Hastings algorithm. 
 

Classes in de.jstacs.classifier.scoringFunctionBased.gendismix used by de.jstacs.classifier.scoringFunctionBased.gendismix
GenDisMixClassifier
          This class implements a classifier the optimizes the following function
\[f(\underline{\lambda}|C,D,\underline{\alpha},\underline{\beta})
The weights $\beta_i$ have to sum to 1.
GenDisMixClassifierParameterSet
          This class contains the parameters for the GenDisMixClassifier.
LearningPrinciple
          This enum can be used to obtain the weights for well-known optimization tasks.
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.
 

Classes in de.jstacs.classifier.scoringFunctionBased.gendismix used by de.jstacs.classifier.scoringFunctionBased.msp
GenDisMixClassifier
          This class implements a classifier the optimizes the following function
\[f(\underline{\lambda}|C,D,\underline{\alpha},\underline{\beta})
The weights $\beta_i$ have to sum to 1.
GenDisMixClassifierParameterSet
          This class contains the parameters for the GenDisMixClassifier.
 

Classes in de.jstacs.classifier.scoringFunctionBased.gendismix used by de.jstacs.classifier.scoringFunctionBased.sampling
GenDisMixClassifier
          This class implements a classifier the optimizes the following function
\[f(\underline{\lambda}|C,D,\underline{\alpha},\underline{\beta})
The weights $\beta_i$ have to sum to 1.
GenDisMixClassifierParameterSet
          This class contains the parameters for the GenDisMixClassifier.
LearningPrinciple
          This enum can be used to obtain the weights for well-known optimization tasks.
 

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