gnu: Add lightgbm.
* gnu/packages/machine-learning.scm (lightgbm): New variable. Signed-off-by: Ludovic Courtès <ludo@gnu.org>master
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@ -47,6 +47,7 @@
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#:use-module (gnu packages gcc)
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#:use-module (gnu packages gcc)
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#:use-module (gnu packages image)
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#:use-module (gnu packages image)
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#:use-module (gnu packages maths)
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#:use-module (gnu packages maths)
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#:use-module (gnu packages mpi)
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#:use-module (gnu packages ocaml)
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#:use-module (gnu packages ocaml)
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#:use-module (gnu packages perl)
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#:use-module (gnu packages perl)
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#:use-module (gnu packages pkg-config)
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#:use-module (gnu packages pkg-config)
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@ -786,3 +787,49 @@ main intended application of Autograd is gradient-based optimization.")
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(define-public python2-autograd
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(define-public python2-autograd
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(package-with-python2 python-autograd))
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(package-with-python2 python-autograd))
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(define-public lightgbm
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(package
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(name "lightgbm")
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(version "2.0.12")
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(source (origin
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(method url-fetch)
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(uri (string-append
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"https://github.com/Microsoft/LightGBM/archive/v"
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version ".tar.gz"))
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(sha256
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(base32
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"132zf0yk0545mg72hyzxm102g3hpb6ixx9hnf8zd2k55gas6cjj1"))
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(file-name (string-append name "-" version ".tar.gz"))))
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(native-inputs
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`(("python-pytest" ,python-pytest)
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("python-nose" ,python-nose)))
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(inputs
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`(("openmpi" ,openmpi)))
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(propagated-inputs
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`(("python-numpy" ,python-numpy)
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("python-scipy" ,python-scipy)))
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(arguments
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`(#:configure-flags
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'("-DUSE_MPI=ON")
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#:phases
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(modify-phases %standard-phases
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(replace 'check
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(lambda* (#:key outputs #:allow-other-keys)
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(with-directory-excursion ,(string-append "../LightGBM-" version)
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(invoke "pytest" "tests/c_api_test/test_.py")))))))
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(build-system cmake-build-system)
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(home-page "https://github.com/Microsoft/LightGBM")
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(synopsis "Gradient boosting framework based on decision tree algorithms")
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(description "LightGBM is a gradient boosting framework that uses tree
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based learning algorithms. It is designed to be distributed and efficient with
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the following advantages:
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@itemize
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@item Faster training speed and higher efficiency
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@item Lower memory usage
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@item Better accuracy
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@item Parallel and GPU learning supported (not enabled in this package)
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@item Capable of handling large-scale data
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@end itemize\n")
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(license license:expat)))
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