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DBHC: Sequence Clustering with Discrete-Output HMMs
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.
Getting started
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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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