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Packages that use TransitionWithSufficientStatistic | |
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de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions | The package provides all interfaces and classes for transitions used in hidden Markov models. |
Uses of TransitionWithSufficientStatistic in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions |
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Subinterfaces of TransitionWithSufficientStatistic in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions | |
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interface |
SamplingTransition
This interface declares all method used during a sampling. |
interface |
TrainableAndDifferentiableTransition
This interface unifies the interfaces TrainableTransition and DifferentiableTransition . |
interface |
TrainableTransition
This class declares methods that allow for estimating the parameters from a sufficient statistic, as for instance done in the (modified) Baum-Welch algorithm, viterbi training, or Gibbs sampling. |
Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions that implement TransitionWithSufficientStatistic | |
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class |
BasicHigherOrderTransition
This class implements the basic transition that allows to be trained using the viterbi or the Baum-Welch algorithm. |
class |
HigherOrderTransition
This class can be used in any AbstractHMM allowing to use gradient based or sampling training algorithm. |
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