Package | Description |
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de.jstacs.classifiers.differentiableSequenceScoreBased.sampling |
Provides the classes for
AbstractScoreBasedClassifier s that are based on
SamplingDifferentiableStatisticalModel s
and that sample parameters using the Metropolis-Hastings algorithm. |
Constructor and Description |
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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. |