hmm: A hidden markov model library

[ algorithms, bsd3, data-mining, library, machine-learning ] [ Propose Tags ]

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.

Modules

[Index]

Downloads

Maintainer's Corner

Package maintainers

For package maintainers and hackage trustees

Candidates

  • No Candidates
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 3602 total (14 in the last 30 days)
Rating (no votes yet) [estimated by Bayesian average]
Your Rating
  • λ
  • λ
  • λ
Status Docs uploaded by user
Build status unknown [no reports yet]