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## Package de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training

The package provides all classes used to determine the training algorithm of a hidden Markov model

See:
Description

Class Summary
BaumWelchParameterSet | This class implements an `HMMTrainingParameterSet` for the Baum-Welch training of an `AbstractHMM`.
HMMTrainingParameterSet | This class implements an abstract `ParameterSet` that is used for the training of an `AbstractHMM`.
MaxHMMTrainingParameterSet | This class is the super class for any `HMMTrainingParameterSet` that is used for a maximizing training algorithm of a hidden Markov model.
MultiThreadedTrainingParameterSet | This class is the super class for any `MaxHMMTrainingParameterSet` that is used for a multi-threaded maximizing training algorithm of a hidden Markov model.
NumericalHMMTrainingParameterSet | This class implements an `ParameterSet` for numerical training of an `AbstractHMM`.
SamplingHMMTrainingParameterSet | This class contains the parameters for training training an `AbstractHMM` using a sampling strategy.
ViterbiParameterSet | This class implements an `ParameterSet` for the viterbi training of an `AbstractHMM`.

## Package de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training Description

The package provides all classes used to determine the training algorithm of a hidden Markov model.

Since:
  Jstacs 1.5
See Also:
  `HMMTrainingParameterSet`

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