Uses of Interface
de.jstacs.models.hmm.Transition

Packages that use Transition

de.jstacs.models.hmm	The package provides all interfaces and classes for a hidden Markov model (HMM).
de.jstacs.models.hmm.transitions	The package provides all interfaces and classes for transitions used in hidden Markov models.

Uses of Transition in de.jstacs.models.hmm

Fields in de.jstacs.models.hmm declared as Transition

protected Transition

AbstractHMM.transition The transitions between all (hidden) states of the HMM.

Methods in de.jstacs.models.hmm that return Transition

Transition

Transition.clone() This method returns a deep clone of the current instance.

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

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

interface	DifferentiableTransition This class declares methods that allow for optimizing the parameters numerically using the Optimizer.
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.
interface	TransitionWithSufficientStatistic This interface defines method for reseting and filling an internal sufficient statistic.

Classes in de.jstacs.models.hmm.transitions that implement Transition

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.