33 lines
1.6 KiB
Python
33 lines
1.6 KiB
Python
# Copyright 2013-2021 Lawrence Livermore National Security, LLC and other
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# Spack Project Developers. See the top-level COPYRIGHT file for details.
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#
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# SPDX-License-Identifier: (Apache-2.0 OR MIT)
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from spack import *
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class RGlmnet(RPackage):
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"""Lasso and Elastic-Net Regularized Generalized Linear Models
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Extremely efficient procedures for fitting the entire lasso or
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elastic-net regularization path for linear regression, logistic and
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multinomial regression models, Poisson regression and the Cox model. Two
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recent additions are the multiple-response Gaussian, and the grouped
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multinomial. The algorithm uses cyclical coordinate descent in a path-wise
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fashion, as described in the paper linked to via the URL below."""
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homepage = "https://cloud.r-project.org/package=glmnet"
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url = "https://cloud.r-project.org/src/contrib/glmnet_2.0-13.tar.gz"
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list_url = "https://cloud.r-project.org/src/contrib/Archive/glmnet"
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version('4.1', sha256='8f0af50919f488789ecf261f6e0907f367d89fca812baa2f814054fb2d0e40cb')
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version('2.0-18', sha256='e8dce9d7b8105f9cc18ba981d420de64a53b09abee219660d3612915d554256b')
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version('2.0-13', sha256='f3288dcaddb2f7014d42b755bede6563f73c17bc87f8292c2ef7776cb9b9b8fd')
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version('2.0-5', sha256='2ca95352c8fbd93aa7800f3d972ee6c1a5fcfeabc6be8c10deee0cb457fd77b1')
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depends_on('r@3.6.0:', when='@4.1:', type=('build', 'run'))
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depends_on('r-matrix@1.0-6:', type=('build', 'run'))
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depends_on('r-foreach', type=('build', 'run'))
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depends_on('r-shape', when='@4.1:', type=('build', 'run'))
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depends_on('r-survival', when='@4.1:', type=('build', 'run'))
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