| Package | Description |
|---|---|
| de.jstacs.classifiers.differentiableSequenceScoreBased.sampling |
Provides the classes for
AbstractScoreBasedClassifiers that are based on
SamplingDifferentiableStatisticalModels
and that sample parameters using the Metropolis-Hastings algorithm. |
| Constructor and Description |
|---|
SamplingGenDisMixClassifier(SamplingGenDisMixClassifierParameterSet params,
BurnInTest burnInTest,
double[] classVariances,
LogPrior prior,
double[] beta,
SamplingDifferentiableStatisticalModel... scoringFunctions)
Creates a new
SamplingGenDisMixClassifier using the external parameters
params, a burn-in test, a set of sampling variances for the different classes,
a prior on the parameters, weights beta for the three components of the
LogGenDisMixFunction, i.e., likelihood, conditional likelihood, and prior,
and scoring functions that model the distribution for each of the classes. |
SamplingGenDisMixClassifier(SamplingGenDisMixClassifierParameterSet params,
BurnInTest burnInTest,
double[] classVariances,
LogPrior prior,
LearningPrinciple principle,
SamplingDifferentiableStatisticalModel... scoringFunctions)
Creates a new
SamplingGenDisMixClassifier using the external parameters
params, a burn-in test, a set of sampling variances for the different classes,
a prior on the parameters, a learning principle,
and scoring functions that model the distribution for each of the classes. |