Uses of Interface
de.jstacs.models.hmm.transitions.TransitionWithSufficientStatistic

Packages that use TransitionWithSufficientStatistic

de.jstacs.models.hmm.transitions

The package provides all interfaces and classes for transitions used in hidden Markov models.

Uses of TransitionWithSufficientStatistic in de.jstacs.models.hmm.transitions

Subinterfaces of TransitionWithSufficientStatistic in de.jstacs.models.hmm.transitions

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.models.hmm.transitions that implement TransitionWithSufficientStatistic

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.