Uses of Class
de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior

Packages that use 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 
 

Uses of LogPrior in de.jstacs.classifier.scoringFunctionBased.cll
 

Fields in de.jstacs.classifier.scoringFunctionBased.cll declared as LogPrior
protected  LogPrior CLLClassifier.prior
          The prior that is used in this instance.
 

Methods in de.jstacs.classifier.scoringFunctionBased.cll with parameters of type LogPrior
static CLLClassifier[] CLLClassifier.create(CLLClassifierParameterSet params, LogPrior prior, ScoringFunction[]... functions)
          This method creates an array of CLLClassifier by using the cross-product of the given ScoringFunctions.
 void CLLClassifier.setPrior(LogPrior prior)
          This method set a new prior that should be used for optimization.
 

Constructors in de.jstacs.classifier.scoringFunctionBased.cll with parameters of type LogPrior
CLLClassifier(CLLClassifierParameterSet params, LogPrior prior, ScoringFunction... score)
          The default constructor.
NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, LogPrior prior, boolean norm, boolean freeParams)
          The constructor creates an instance using the given prior.
 

Uses of LogPrior in de.jstacs.classifier.scoringFunctionBased.logPrior
 

Subclasses of LogPrior in de.jstacs.classifier.scoringFunctionBased.logPrior
 class DoesNothingLogPrior
          This class defines a LogPrior that does not penalize any parameter.
 class SeparateGaussianLogPrior
          Class for a LogPrior that defines a Gaussian prior on the parameters of a set of NormalizableScoringFunctions and a set of class-parameters.
 class SeparateLaplaceLogPrior
          Class for a LogPrior that defines a Laplace-prior on the parameters of a set of NormalizableScoringFunctions and a set of class-parameters.
 class SeparateLogPrior
          Abstract class for priors that penalize each parameter value independently and have some variance (and possible mean) as hyper-parameters.
 class SimpleGaussianSumLogPrior
          This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter.
 

Methods in de.jstacs.classifier.scoringFunctionBased.logPrior that return LogPrior
abstract  LogPrior LogPrior.getNewInstance()
          This method returns an empty new instance of the current prior.
 LogPrior DoesNothingLogPrior.getNewInstance()