Python Hidden Markov model implementation
logilab-hmm is an implementation of Hidden Markov model and associated algorithms (Viterbi and Baum-Welsh).
logilab-hmm is an implementation of Hidden Markov model and associated algorithms (Viterbi and Baum-Welsh).
Version: 0.5.0
License: GPL-2+
GitHub
| Maintainers |
No Maintainer
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| Categories |
python
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| Homepage |
http://www.logilab.org/project/logilab-hmm
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| Platforms |
darwin
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| Variants |
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clang10
(Build using the MacPorts clang 10 compiler)
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clang11
(Build using the MacPorts clang 11 compiler)
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clang12
(Build using the MacPorts clang 12 compiler)
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clang50
(Build using the MacPorts clang 5.0 compiler)
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clang60
(Build using the MacPorts clang 6.0 compiler)
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clang70
(Build using the MacPorts clang 7.0 compiler)
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clang80
(Build using the MacPorts clang 8.0 compiler)
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clang90
(Build using the MacPorts clang 9.0 compiler)
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clangdevel
(Build using the MacPorts clang devel compiler)
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g95
(Build using the g95 Fortran compiler)
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gcc10
(Build using the MacPorts gcc 10 compiler)
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gcc11
(Build using the MacPorts gcc 11 compiler)
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gcc5
(Build using the MacPorts gcc 5 compiler)
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gcc6
(Build using the MacPorts gcc 6 compiler)
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gcc7
(Build using the MacPorts gcc 7 compiler)
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gcc8
(Build using the MacPorts gcc 8 compiler)
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gcc9
(Build using the MacPorts gcc 9 compiler)
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gccdevel
(Build using the MacPorts gcc devel compiler)
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gfortran
(Build using the MacPorts gcc 11 Fortran compiler)
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Subport(s) (1)
"py27-logilab-hmm" depends on
lib (4)
build (2)
Ports that depend on "py27-logilab-hmm"
lib (1)
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