Uses of Interface
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

Packages that use Transition

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

Uses of Transition in de.jstacs.sequenceScores.statisticalModels.trainable.hmm

Fields in de.jstacs.sequenceScores.statisticalModels.trainable.hmm declared as Transition

protected Transition

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

Uses of Transition in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions

Subinterfaces of Transition in de.jstacs.sequenceScores.statisticalModels.trainable.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.sequenceScores.statisticalModels.trainable.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.

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions that return Transition

Transition

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

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions with parameters of type Transition

void	TransitionWithSufficientStatistic.joinStatistics(Transition... transitions) This method joins the statistics of different instances and sets this joined statistic as statistic of each instance.
void	BasicHigherOrderTransition.joinStatistics(Transition... transitions)
void	Transition.setParameters(Transition t) Set values of parameters of the instance to the value of the parameters of the given instance.
void	BasicHigherOrderTransition.setParameters(Transition t)