Uses of Class
dev.nm.stat.hmm.mixture.MixtureHMM
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Packages that use MixtureHMM Package Description dev.nm.stat.hmm.mixture -
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Uses of MixtureHMM in dev.nm.stat.hmm.mixture
Subclasses of MixtureHMM in dev.nm.stat.hmm.mixture Modifier and Type Class 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 Description MixtureHMM
MixtureHMMEM.TrainedModel. model
the newly trained model as a result of the EM algorithmMethods in dev.nm.stat.hmm.mixture with parameters of type MixtureHMM Modifier and Type Method 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 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.
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