Uses of Class
dev.nm.stat.hmm.mixture.MixtureHMM

Packages that use MixtureHMM

Package	Description
dev.nm.stat.hmm.mixture

Uses of MixtureHMM in dev.nm.stat.hmm.mixture

Subclasses of MixtureHMM in dev.nm.stat.hmm.mixture

Modifier and Type	Class and Description
class	MixtureHMMEM The EM algorithm is used to find the unknown parameters of a hidden Markov model (HMM) by making use of the forward-backward algorithm.

Fields in dev.nm.stat.hmm.mixture declared as MixtureHMM

Modifier and Type	Field and Description
MixtureHMM	MixtureHMMEM.TrainedModel.model the newly trained model as a result of the EM algorithm

Methods in dev.nm.stat.hmm.mixture with parameters of type MixtureHMM

Modifier and Type	Method and Description
static MixtureHMMEM.TrainedModel	MixtureHMMEM.train(MixtureHMM model0, double[] observations) Constructs a trained mixture hidden Markov model, one iteration.

Constructors in dev.nm.stat.hmm.mixture with parameters of type MixtureHMM

Constructor and Description
MixtureHMM(MixtureHMM model) Copy constructor.
MixtureHMMEM(double[] observations, MixtureHMM model0, double epsilon, int maxIterations) Constructs a mixture HMM model by training an initial model using the Baum-Welch algorithm.