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.