learning-hmm: Yet another library for hidden Markov models

[ algorithms, library, machine-learning, mit, statistics ] [ Propose Tags ]

This library provides functions for the maximum likelihood estimation of discrete hidden Markov models. At present, only Baum-Welch and Viterbi algorithms are implemented for the plain HMM and the input-output HMM.


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Change log CHANGES.md
Dependencies base (>=4.7 && <5), containers, deepseq, hmatrix (>=0.16), random-fu, random-source, vector [details]
License MIT
Copyright Copyright (c) 2014-2015 Mitsuhiro Nakamura
Author Mitsuhiro Nakamura
Maintainer Mitsuhiro Nakamura <m.nacamura@gmail.com>
Category Algorithms, Machine Learning, Statistics
Home page https://github.com/mnacamura/learning-hmm
Source repo head: git clone https://github.com/mnacamura/learning-hmm.git
Uploaded by mnacamura at 2015-04-05T13:13:18Z
Reverse Dependencies 1 direct, 0 indirect [details]
Downloads 8793 total (48 in the last 30 days)
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Status Docs available [build log]
Last success reported on 2015-04-05 [all 1 reports]