Uses of Package
de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior

Packages that use de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior

de.jstacs.classifiers.differentiableSequenceScoreBased	Provides the classes for Classifiers that are based on SequenceScores. It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior.
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix	Provides an implementation of a classifier that allows to train the parameters of a set of DifferentiableStatisticalModels by a unified generative-discriminative learning principle.
de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior	Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors.
de.jstacs.classifiers.differentiableSequenceScoreBased.msp	Provides an implementation of a classifier that allows to train the parameters of a set of DifferentiableStatisticalModels either by maximum supervised posterior (MSP) or by maximum conditional likelihood (MCL).
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling	Provides the classes for AbstractScoreBasedClassifiers that are based on SamplingDifferentiableStatisticalModels and that sample parameters using the Metropolis-Hastings algorithm.

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior used by de.jstacs.classifiers.differentiableSequenceScoreBased

LogPrior
The abstract class for any log-prior used e.g.

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior used by de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

LogPrior
The abstract class for any log-prior used e.g.

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior used by de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior

CompositeLogPrior
This class implements a composite prior that can be used for DifferentiableStatisticalModel.

DoesNothingLogPrior
This class defines a LogPrior that does not penalize any parameter.

LogPrior
The abstract class for any log-prior used e.g.

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.

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior used by de.jstacs.classifiers.differentiableSequenceScoreBased.msp

LogPrior
The abstract class for any log-prior used e.g.

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior used by de.jstacs.classifiers.differentiableSequenceScoreBased.sampling

LogPrior
The abstract class for any log-prior used e.g.