# This file created by conda-build 3.18.9
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Tue Aug  6 15:50:44 2019
# ------------------------------------------------

package:
    name: r-mlr
    version: 2.15.0
source:
    sha256: a3c2c2bd65a87d90b5e5e877b1ef8e7712e76b4eb1660d3f69672a1860ca5324
    url:
        - https://cran.r-project.org/src/contrib/Archive/mlr/mlr_2.15.0.tar.gz
        - https://cran.r-project.org/src/contrib/mlr_2.15.0.tar.gz
build:
    merge_build_host: true
    number: '0'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r35hda5aaf8_0
requirements:
    build:
        - m2-bash 4.3.042 5
        - m2-coreutils 8.25 102
        - m2-filesystem 2016.04 4
        - m2-gcc-libs 5.3.0 4
        - m2-gmp 6.1.0 3
        - m2-libbz2 1.0.6 3
        - m2-libiconv 1.14 3
        - m2-libintl 0.19.7 4
        - m2-make 4.1 5
        - m2-msys2-runtime 2.5.0.17080.65c939c 3
        - m2-sed 4.2.2 3
        - m2-zip 3.0 2
        - m2w64-binutils 2.25.1 5
        - m2w64-bzip2 1.0.6 6
        - m2w64-crt-git 5.0.0.4636.2595836 2
        - m2w64-gcc 5.3.0 6
        - m2w64-gcc-ada 5.3.0 6
        - m2w64-gcc-fortran 5.3.0 6
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2w64-gcc-libs 5.3.0 7
        - m2w64-gcc-libs-core 5.3.0 7
        - m2w64-gcc-objc 5.3.0 6
        - m2w64-gmp 6.1.0 2
        - m2w64-headers-git 5.0.0.4636.c0ad18a 2
        - m2w64-isl 0.16.1 2
        - m2w64-libiconv 1.14 6
        - m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-make 4.1.2351.a80a8b8 2
        - m2w64-mpc 1.0.3 3
        - m2w64-mpfr 3.1.4 4
        - m2w64-pkg-config 0.29.1 2
        - m2w64-toolchain 5.3.0 7
        - m2w64-toolchain_win-64 2.4.0 0
        - m2w64-tools-git 5.0.0.4592.90b8472 2
        - m2w64-windows-default-manifest 6.4 3
        - m2w64-winpthreads-git 5.0.0.4634.697f757 2
        - m2w64-zlib 1.2.8 10
        - msys2-conda-epoch 20160418 1
    host:
        - _r-mutex 1.0.1 anacondar_1
        - libiconv 1.15 hfa6e2cd_1005
        - libxml2 2.9.9 h9ce36c8_2
        - m2w64-bwidget 1.9.10 2
        - m2w64-bzip2 1.0.6 6
        - m2w64-expat 2.1.1 2
        - m2w64-fftw 3.3.4 6
        - m2w64-flac 1.3.1 3
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2w64-gcc-libs 5.3.0 7
        - m2w64-gcc-libs-core 5.3.0 7
        - m2w64-gettext 0.19.7 2
        - m2w64-gmp 6.1.0 2
        - m2w64-gsl 2.1 2
        - m2w64-icu 58.2 heb44b8b_2
        - m2w64-libiconv 1.14 6
        - m2w64-libjpeg-turbo 1.4.2 3
        - m2w64-libogg 1.3.2 3
        - m2w64-libpng 1.6.21 2
        - m2w64-libsndfile 1.0.26 2
        - m2w64-libtiff 4.0.6 2
        - m2w64-libvorbis 1.3.5 2
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-libxml2 2.9.3 4
        - m2w64-mpfr 3.1.4 4
        - m2w64-openblas 0.2.19 1
        - m2w64-pcre 8.38 2
        - m2w64-speex 1.2rc2 3
        - m2w64-speexdsp 1.2rc3 3
        - m2w64-tcl 8.6.5 3
        - m2w64-tk 8.6.5 3
        - m2w64-tktable 2.10 5
        - m2w64-wineditline 2.101 5
        - m2w64-xz 5.2.2 2
        - m2w64-zlib 1.2.8 10
        - msys2-conda-epoch 20160418 1
        - r-assertthat 0.2.1 r35h6115d3f_1
        - r-backports 1.1.4 r35hda5aaf8_1
        - r-base 3.5.1 h62da294_1009
        - r-bbmisc 1.11 r35hda5aaf8_1002
        - r-checkmate 1.9.4 r35hda5aaf8_1
        - r-cli 1.1.0 r35h6115d3f_1
        - r-colorspace 1.4_1 r35hda5aaf8_1
        - r-crayon 1.3.4 r35h6115d3f_1002
        - r-data.table 1.12.2 r35hda5aaf8_1
        - r-digest 0.6.20 r35h796a38f_1
        - r-ellipsis 0.2.0.1 r35hda5aaf8_1
        - r-fansi 0.4.0 r35hda5aaf8_1001
        - r-fastmatch 1.1_0 r35hda5aaf8_1004
        - r-ggplot2 3.2.0 r35h6115d3f_1
        - r-glue 1.3.1 r35hda5aaf8_1
        - r-gtable 0.3.0 r35h6115d3f_2
        - r-labeling 0.3 r35h6115d3f_1002
        - r-lattice 0.20_38 r35hda5aaf8_1002
        - r-lazyeval 0.2.2 r35hda5aaf8_1
        - r-magrittr 1.5 r35h6115d3f_1002
        - r-mass 7.3_51.4 r35hda5aaf8_1
        - r-matrix 1.2_17 r35hda5aaf8_1
        - r-mgcv 1.8_28 r35hda5aaf8_1
        - r-munsell 0.5.0 r35h6115d3f_1002
        - r-nlme 3.1_140 r35h17ddedb_1
        - r-parallelmap 1.4 r35h6115d3f_1
        - r-paramhelpers 1.12 r35hda5aaf8_1
        - r-pillar 1.4.2 r35h6115d3f_2
        - r-pkgconfig 2.0.2 r35h6115d3f_1002
        - r-plyr 1.8.4 r35h796a38f_1003
        - r-r6 2.4.0 r35h6115d3f_2
        - r-rcolorbrewer 1.1_2 r35h6115d3f_1002
        - r-rcpp 1.0.2 r35h796a38f_0
        - r-reshape2 1.4.3 r35h796a38f_1004
        - r-rlang 0.4.0 r35hda5aaf8_1
        - r-scales 1.0.0 r35h796a38f_1002
        - r-stringi 1.4.3 r35h796a38f_3
        - r-stringr 1.4.0 r35h6115d3f_1
        - r-survival 2.44_1.1 r35hda5aaf8_1
        - r-tibble 2.1.3 r35hda5aaf8_1
        - r-utf8 1.1.4 r35hda5aaf8_1001
        - r-vctrs 0.2.0 r35hda5aaf8_1
        - r-viridislite 0.3.0 r35h6115d3f_1002
        - r-withr 2.1.2 r35h6115d3f_1001
        - r-xml 3.98_1.20 r35hda5aaf8_1
        - r-zeallot 0.1.0 r35h6115d3f_1001
        - vc 14.1 h0510ff6_4
        - vs2015_runtime 14.15.26706 h3a45250_4
        - zlib 1.2.11 h2fa13f4_1005
    run:
        - m2w64-gcc-libs
        - r-backports >=1.1.0
        - r-base >=3.5,<3.6.0a0
        - r-bbmisc >=1.11
        - r-checkmate >=1.8.2
        - r-data.table
        - r-ggplot2
        - r-parallelmap >=1.3
        - r-paramhelpers >=1.10
        - r-stringi
        - r-survival
        - r-xml
test:
    commands:
        - '"%R%" -e "library(''mlr'')"'
about:
    home: https://github.com/mlr-org/mlr
    license: BSD_2_clause
    license_family: BSD
    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.
extra:
    copy_test_source_files: true
    final: true
    recipe-maintainers:
        - conda-forge/r
