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hmm: A hidden markov model library
hmm: A hidden markov model library
Data.HMM is a library for using Hidden Markov Models with Haskell. Commonly used algoriths (i.e. the forward and backwards algorithms, Viterbi, and Baum-Welch) are implemented. The best way to learn to use it is to visit the tutorial at http://izbicki.me/blog/using-hmms-in-haskell-for-bioinformatics. The tutorial also includes performance benchmarks that you should be aware of.
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Versions [RSS] 0.1, 0.1.1, 0.2.1, 0.2.1.1 Dependencies array, base (>=4 && <5), data-memocombinators, list-extras, logfloat [details] License BSD-3-Clause Author Mike Izbicki Maintainer mike@izbicki.me Category Algorithms, Data mining, Machine learning Home page https://github.com/mikeizbicki/hmm Uploaded by MikeIzbicki at 2012-03-26T19:37:56Z Distributions Reverse Dependencies 1 direct, 0 indirect [details] Downloads 3745 total (3 in the last 30 days) Rating (no votes yet) [estimated by Bayesian average] Your Rating
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