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.