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.
|Author||Gabriel Budel [aut, cre], Flavius Frasincar [aut]|
|Maintainer||Gabriel Budel <[email protected]>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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