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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
CompositeLogPrior This class implements a composite prior that can be used for NormalizableScoringFunction.
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 variances (and possible means) as hyperparameters.
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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