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## Uses of Package
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states

Packages that use de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states
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.states | The package provides all interfaces and classes for states used in hidden Markov models.

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states used by de.jstacs.sequenceScores.statisticalModels.trainable.hmm
State This interface declares the methods of any state used in a hidden Markov model.

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states used by de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states
DifferentiableState This interface declares a method that allows to evaluate the gradient which is essential for numerical optimization.
SamplingState
SimpleState This class implements a `State` based on `Emission` that allows to reuse `Emission`s for different `State`s.
State This interface declares the methods of any state used in a hidden Markov model.
TrainableState This class implements method that allows to fill a statistic, which is used to estimate the parameters of a state during, for instance, the Baum-Welch training.

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