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Additional r packages (#7892)

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* Add r-bbmisc

* Add r-dicekriging

* Add r-lhs

* Add r-mco

* Add r-misc3d

* Add r-mlr

* Remove boilerplate from r-mlr package

* Add r-mlrMBO

* Add r-parallelmap

* Add r-paramhelpers

* Add r-plot3d

* Add r-rgenoud

* Add r-smoof

* Add r-rinside 0.2.14

* Fix flake8 issues

* Add specific required versions

* Add more up-to-date versions of r-{mco, mlr, mlrMBO, smoof}
This commit is contained in:
mcneish1
2018-04-25 18:59:46 -07:00
committed by Adam J. Stewart
parent 28901c8104
commit 94afb2430c
13 changed files with 509 additions and 3 deletions
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var/spack/repos/builtin/packages/r-mlr/package.py Normal file
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##############################################################################
# Copyright (c) 2013-2018, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
#
# This file is part of Spack.
# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
# LLNL-CODE-647188
#
# For details, see https://github.com/spack/spack
# Please also see the NOTICE and LICENSE files for our notice and the LGPL.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License (as
# published by the Free Software Foundation) version 2.1, February 1999.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and
# conditions of the GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
##############################################################################
from spack import *
class RMlr(RPackage):
"""Interface to a large number of classification and regression techniques,
including machine-readable parameter descriptions. There is also an
experimental extension for survival analysis, clustering and general,
example-specific cost-sensitive learning. Generic resampling,
including cross-validation, bootstrapping and subsampling.
Hyperparameter tuning with modern optimization techniques,
for single- and multi-objective problems. Filter and wrapper methods for
feature selection. Extension of basic learners with additional
operations common in machine learning, also allowing for easy nested
resampling. Most operations can be parallelized."""
homepage = "https://github.com/mlr-org/mlr/"
url = "https://cran.r-project.org/src/contrib/mlr_2.12.1.tar.gz"
list_url = "https://cran.r-project.org/src/contrib/Archive/mlr"
version('2.12.1', 'abddfc9dfe95f290a233ecd97969a4ec')
version('2.12', '94ee7495aeafb432c8af5a8bdd26c25f')
depends_on('r-paramhelpers@1.10:', type=('build', 'run'))
depends_on('r-bbmisc@1.11:', type=('build', 'run'))
depends_on('r-backports@1.1.0:', type=('build', 'run'))
depends_on('r-ggplot2', type=('build', 'run'))
depends_on('r-stringi', type=('build', 'run'))
depends_on('r-checkmate@1.8.2:', type=('build', 'run'))
depends_on('r-data-table', type=('build', 'run'))
depends_on('r-parallelmap@1.3:', type=('build', 'run'))
depends_on('r-xml', type=('build', 'run'))