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Provides an implementation of a mixture of hidden Markov models (HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering (DBHC) algorithm. The DBHC algorithm is an HMM Clustering algorithm that finds a mixture of discrete-output HMMs while using heuristics based on Bayesian Information Criterion (BIC) to search for the optimal number of HMM states and the optimal number of clusters.
Package details |
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Author | Gabriel Budel [aut, cre], Flavius Frasincar [aut] |
Maintainer | Gabriel Budel <gabysp_budel@hotmail.com> |
License | GPL (>= 3) |
Version | 0.0.3 |
URL | https://github.com/gabybudel/DBHC |
Package repository | View on CRAN |
Installation |
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