{% set version = "2.16.0" %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

package:
  name: r-mlr
  version: {{ version|replace("-", "_") }}

source:
  url:
    - {{ cran_mirror }}/src/contrib/mlr_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/mlr/mlr_{{ version }}.tar.gz
  sha256: 3db8141d9cbb71139c9bf3a3ea995524322512221b56e6bcf44338d24f84e76a

build:
  merge_build_host: True  # [win]
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/

requirements:
  build:
    - {{ compiler('c') }}              # [not win]
    - {{ compiler('m2w64_c') }}        # [win]
    - {{posix}}filesystem        # [win]
    - {{posix}}make
    - {{posix}}sed               # [win]
    - {{posix}}coreutils         # [win]
    - {{posix}}zip               # [win]
  host:
    - r-base
    - r-bbmisc >=1.11
    - r-paramhelpers >=1.10
    - r-xml
    - r-backports >=1.1.0
    - r-checkmate >=1.8.2
    - r-data.table
    - r-ggplot2
    - r-parallelmap >=1.3
    - r-stringi
    - r-survival
  run:
    - r-base
    - {{native}}gcc-libs         # [win]
    - r-bbmisc >=1.11
    - r-paramhelpers >=1.10
    - r-xml
    - r-backports >=1.1.0
    - r-checkmate >=1.8.2
    - r-data.table
    - r-ggplot2
    - r-parallelmap >=1.3
    - r-stringi
    - r-survival

test:
  commands:
    - $R -e "library('mlr')"           # [not win]
    - "\"%R%\" -e \"library('mlr')\""  # [win]

about:
  home: https://github.com/mlr-org/mlr
  license: BSD_2_clause
  license_file: LICENSE
  summary: 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.
  license_family: BSD

extra:
  recipe-maintainers:
    - conda-forge/r

# Package: mlr
# Title: Machine Learning in R
# Version: 2.14.0
# Authors@R:  c(person(given = "Bernd", family = "Bischl", role = "aut", email = "bernd_bischl@gmx.net", comment = c(ORCID = "0000-0001-6002-6980")), person(given = "Michel", family = "Lang", role = "aut", email = "michellang@gmail.com", comment = c(ORCID = "0000-0001-9754-0393")), person(given = "Lars", family = "Kotthoff", role = "aut", email = "larsko@uwyo.edu"), person(given = "Julia", family = "Schiffner", role = "aut", email = "schiffner@math.uni-duesseldorf.de"), person(given = "Jakob", family = "Richter", role = "aut", email = "code@jakob-r.de"), person(given = "Zachary", family = "Jones", role = "aut", email = "zmj@zmjones.com"), person(given = "Giuseppe", family = "Casalicchio", role = "aut", email = "giuseppe.casalicchio@stat.uni-muenchen.de", comment = c(ORCID = "0000-0001-5324-5966")), person(given = "Mason", family = "Gallo", role = "aut", email = "masonagallo@gmail.com"), person(given = "Patrick", family = "Schratz", role = c("aut", "cre"), email = "patrick.schratz@gmail.com", comment = c(ORCID = "0000-0003-0748-6624")), person(given = "Jakob", family = "Bossek", role = "ctb", email = "jakob.bossek@tu-dortmund.de", comment = c(ORCID = "0000-0002-4121-4668")), person(given = "Erich", family = "Studerus", role = "ctb", email = "erich.studerus@upkbs.ch", comment = c(ORCID = "0000-0003-4233-0182")), person(given = "Leonard", family = "Judt", role = "ctb", email = "leonard.judt@tu-dortmund.de"), person(given = "Tobias", family = "Kuehn", role = "ctb", email = "tobi.kuehn@gmx.de"), person(given = "Pascal", family = "Kerschke", role = "ctb", email = "kerschke@uni-muenster.de", comment = c(ORCID = "0000-0003-2862-1418")), person(given = "Florian", family = "Fendt", role = "ctb", email = "flo_fendt@gmx.de"), person(given = "Philipp", family = "Probst", role = "ctb", email = "philipp_probst@gmx.de", comment = c(ORCID = "0000-0001-8402-6790")), person(given = "Xudong", family = "Sun", role = "ctb", email = "xudong.sun@stat.uni-muenchen.de", comment = c(ORCID = "0000-0003-3269-2307")), person(given = "Janek", family = "Thomas", role = "ctb", email = "janek.thomas@stat.uni-muenchen.de", comment = c(ORCID = "0000-0003-4511-6245")), person(given = "Bruno", family = "Vieira", role = "ctb", email = "bruno.hebling.vieira@usp.br"), person(given = "Laura", family = "Beggel", role = "ctb", email = "laura.beggel@web.de", comment = c(ORCID = "0000-0002-8872-8535")), person(given = "Quay", family = "Au", role = "ctb", email = "quay.au@stat.uni-muenchen.de", comment = c(ORCID = "0000-0002-5252-8902")), person(given = "Martin", family = "Binder", role = "ctb", email = "ma.binder@campus.lmu.de"), person(given = "Florian", family = "Pfisterer", role = "ctb", email = "pfistererf@googlemail.com"), person(given = "Stefan", family = "Coors", role = "ctb", email = "stefan.coors@gmx.net"), person(given = "Steve", family = "Bronder", role = "ctb", email = "sab2287@columbia.edu"), person(given = "Alexander", family = "Engelhardt", role = "ctb", email = "alexander.w.engelhardt@gmail.com"), person(given = "Christoph", family = "Molnar", role = "ctb", email = "christoph.molnar@stat.uni-muenchen.de"))
# Description: 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.
# License: BSD_2_clause + file LICENSE
# URL: https://github.com/mlr-org/mlr
# BugReports: https://github.com/mlr-org/mlr/issues
# Depends: ParamHelpers (>= 1.10), R (>= 3.0.2)
# Imports: backports (>= 1.1.0), BBmisc (>= 1.11), checkmate (>= 1.8.2), data.table, ggplot2, methods, parallelMap (>= 1.3), stats, stringi, survival, utils, XML
# Suggests: ada, adabag, bartMachine, batchtools, brnn, bst, C50, care, caret (>= 6.0-57), class, clue, cluster, clusterSim (>= 0.44-5), clValid, cmaes, cowplot, CoxBoost, crs, Cubist, deepnet, DiceKriging, DiscriMiner, e1071, earth, elasticnet, emoa, evtree, extraTrees, fda.usc, FDboost, flare, FNN, fpc, frbs, FSelector, FSelectorRcpp (>= 0.2.1), gbm, GenSA, ggpubr, glmnet, GPfit, h2o (>= 3.6.0.8), Hmisc, hrbrthemes, irace (>= 2.0), kernlab, kknn, klaR, knitr, laGP, LiblineaR, lintr (>= 1.0.0.9001), liquidSVM, MASS, mboost, mco, mda, memoise, mlbench, mldr, mlrMBO, mmpf, modeltools, mRMRe, neuralnet, nnet, nodeHarvest (>= 0.7-3), numDeriv, pander, pamr, party, penalized (>= 0.9-47), pls, PMCMR (>= 4.1), praznik (>= 5.0.0), randomForest, randomForestSRC (>= 2.7.0), ranger (>= 0.8.0), rappdirs, refund, rex, rFerns, rgenoud, rknn, rmarkdown, ROCR, rotationForest, rpart, RRF, rrlda, rsm, RSNNS, RWeka, sda, sf, smoof, sparseLDA, stepPlr, survAUC, svglite, SwarmSVM, testthat, tgp, TH.data, wavelets, xgboost (>= 0.6-2)
# VignetteBuilder: knitr
# ByteCompile: yes
# Encoding: UTF-8
# LazyData: yes
# RoxygenNote: 6.1.1
# NeedsCompilation: yes
# Packaged: 2019-04-18 15:33:51 UTC; pjs
# Author: Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Lars Kotthoff [aut], Julia Schiffner [aut], Jakob Richter [aut], Zachary Jones [aut], Giuseppe Casalicchio [aut] (<https://orcid.org/0000-0001-5324-5966>), Mason Gallo [aut], Patrick Schratz [aut, cre] (<https://orcid.org/0000-0003-0748-6624>), Jakob Bossek [ctb] (<https://orcid.org/0000-0002-4121-4668>), Erich Studerus [ctb] (<https://orcid.org/0000-0003-4233-0182>), Leonard Judt [ctb], Tobias Kuehn [ctb], Pascal Kerschke [ctb] (<https://orcid.org/0000-0003-2862-1418>), Florian Fendt [ctb], Philipp Probst [ctb] (<https://orcid.org/0000-0001-8402-6790>), Xudong Sun [ctb] (<https://orcid.org/0000-0003-3269-2307>), Janek Thomas [ctb] (<https://orcid.org/0000-0003-4511-6245>), Bruno Vieira [ctb], Laura Beggel [ctb] (<https://orcid.org/0000-0002-8872-8535>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [ctb], Florian Pfisterer [ctb], Stefan Coors [ctb], Steve Bronder [ctb], Alexander Engelhardt [ctb], Christoph Molnar [ctb]
# Maintainer: Patrick Schratz <patrick.schratz@gmail.com>
# Repository: CRAN
# Date/Publication: 2019-04-25 22:00:04 UTC
