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