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HMMBase is not maintained anymore. It will keep being available as a Julia package but we encourage existing and new users to migrate to HiddenMarkovModels.jl which offers a similar interface. For more information see HiddenMarkovModels.jl: when did HMMs get so fast?. HMMBase provides a lightweight and efficient abstraction for hidden Markov models in Julia. Most HMMs libraries only support discrete (e.g. categorical) or Normal distributions. In contrast HMMBase builds upon Distributions.jl to support arbitrary univariate and multivariate distributions.
Features
- Hidden Markov Models for Julia
- Multi-sequences HMMs, see MS_HMMBase
- Bayesian models, probabilistic programming, see Turing
- Nonparametric models (HDP-H(S)MM, ...)
- Supports any observation distributions conforming to the Distribution interface
- Fast and stable implementations of the forward/backward, EM (Baum-Welch) and Viterbi algorithms
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Data VisualizationLicense
MIT LicenseFollow HMMBase.jl
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