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learning-hmm.cabal
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learning-hmm.cabal
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name: learning-hmm
version: 0.3.2.2
stability: experimental
synopsis: Yet another library for hidden Markov models
description: 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.
category: Algorithms, Machine Learning, Statistics
author: Mitsuhiro Nakamura
maintainer: Mitsuhiro Nakamura <[email protected]>
copyright: Copyright (c) 2014-2015 Mitsuhiro Nakamura
license: MIT
license-file: LICENSE
homepage: https://github.com/mnacamura/learning-hmm
cabal-version: >=1.10
build-type: Simple
extra-source-files: CHANGES.md
source-repository head
type: git
location: https://github.com/mnacamura/learning-hmm.git
library
exposed-modules: Learning.HMM
, Learning.IOHMM
other-modules: Data.Random.Distribution.Extra
, Data.Random.Distribution.Simplex
, Data.Vector.Generic.Extra
, Learning.HMM.Internal
, Learning.IOHMM.Internal
-- other-extensions:
build-depends: base >=4.7 && <5
, containers
, deepseq
, hmatrix >= 0.16
, random-fu
, random-source
, vector
hs-source-dirs: src
default-language: Haskell2010
ghc-options: -Wall