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.
- Version0.0.3
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release12/22/2022
Documentation
Team
Gabriel Budel
Flavius Frasincar
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