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author | Fis Trivial <ybbs.daans@hotmail.com> | 2018-06-12 10:01:16 +0000 |
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committer | Ludovic Courtès <ludo@gnu.org> | 2018-06-14 23:34:59 +0200 |
commit | 112c2c010b2e84691302bdc174d9a4825dc6ca24 (patch) | |
tree | e689559d31880d07e33365bd51fd235289300703 /gnu | |
parent | baed923682802b7281bd68274f080d2bb55d3eff (diff) | |
download | patches-112c2c010b2e84691302bdc174d9a4825dc6ca24.tar patches-112c2c010b2e84691302bdc174d9a4825dc6ca24.tar.gz |
gnu: Add lightgbm.
* gnu/packages/machine-learning.scm (lightgbm): New variable.
Signed-off-by: Ludovic Courtès <ludo@gnu.org>
Diffstat (limited to 'gnu')
-rw-r--r-- | gnu/packages/machine-learning.scm | 47 |
1 files changed, 47 insertions, 0 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index 15e4d45749..cda5c1e2c8 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -47,6 +47,7 @@ #:use-module (gnu packages gcc) #:use-module (gnu packages image) #:use-module (gnu packages maths) + #:use-module (gnu packages mpi) #:use-module (gnu packages ocaml) #:use-module (gnu packages perl) #:use-module (gnu packages pkg-config) @@ -786,3 +787,49 @@ main intended application of Autograd is gradient-based optimization.") (define-public python2-autograd (package-with-python2 python-autograd)) + +(define-public lightgbm + (package + (name "lightgbm") + (version "2.0.12") + (source (origin + (method url-fetch) + (uri (string-append + "https://github.com/Microsoft/LightGBM/archive/v" + version ".tar.gz")) + (sha256 + (base32 + "132zf0yk0545mg72hyzxm102g3hpb6ixx9hnf8zd2k55gas6cjj1")) + (file-name (string-append name "-" version ".tar.gz")))) + (native-inputs + `(("python-pytest" ,python-pytest) + ("python-nose" ,python-nose))) + (inputs + `(("openmpi" ,openmpi))) + (propagated-inputs + `(("python-numpy" ,python-numpy) + ("python-scipy" ,python-scipy))) + (arguments + `(#:configure-flags + '("-DUSE_MPI=ON") + #:phases + (modify-phases %standard-phases + (replace 'check + (lambda* (#:key outputs #:allow-other-keys) + (with-directory-excursion ,(string-append "../LightGBM-" version) + (invoke "pytest" "tests/c_api_test/test_.py"))))))) + (build-system cmake-build-system) + (home-page "https://github.com/Microsoft/LightGBM") + (synopsis "Gradient boosting framework based on decision tree algorithms") + (description "LightGBM is a gradient boosting framework that uses tree +based learning algorithms. It is designed to be distributed and efficient with +the following advantages: + +@itemize +@item Faster training speed and higher efficiency +@item Lower memory usage +@item Better accuracy +@item Parallel and GPU learning supported (not enabled in this package) +@item Capable of handling large-scale data +@end itemize\n") + (license license:expat))) |