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

Package details

AuthorGabriel Budel [aut, cre], Flavius Frasincar [aut]
MaintainerGabriel Budel <gabysp_budel@hotmail.com>
LicenseGPL (>= 3)
URL https://github.com/gabybudel/DBHC
Package repositoryView on CRAN
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DBHC documentation built on Dec. 28, 2022, 2:44 a.m.