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## Uses of Package
de.jstacs.classifier.scoringFunctionBased.logPrior

Packages that use de.jstacs.classifier.scoringFunctionBased.logPrior
de.jstacs.classifier.scoringFunctionBased.cll | Provides the implementation of the log conditional likelihood as an `OptimizableFunction` and a classifier that uses log conditional likelihood or supervised posterior to learn the parameters of a set of `ScoringFunctions`
de.jstacs.classifier.scoringFunctionBased.logPrior | Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors

Classes in de.jstacs.classifier.scoringFunctionBased.logPrior used by de.jstacs.classifier.scoringFunctionBased.cll
LogPrior The abstract class for any log-prior used e.g. for maximum supervised posterior optimization.

Classes in de.jstacs.classifier.scoringFunctionBased.logPrior used by de.jstacs.classifier.scoringFunctionBased.logPrior
DoesNothingLogPrior This class defines a `LogPrior` that does not penalize any parameter.
LogPrior The abstract class for any log-prior used e.g. for maximum supervised posterior optimization.
SeparateLogPrior Abstract class for priors that penalize each parameter value independently and have some variance (and possible mean) as hyper-parameters.
SimpleGaussianSumLogPrior This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter.

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