%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname MachineShop %global packver 3.8.0 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 3.8.0 Release: 1%{?dist}%{?buildtag} Summary: Machine Learning Models and Tools License: GPL-3 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 4.1.0 Requires: R-core >= 4.1.0 BuildRequires: R-CRAN-ggplot2 >= 3.4.0 BuildRequires: R-CRAN-cli >= 3.1.0 BuildRequires: R-CRAN-Matrix >= 1.5.0 BuildRequires: R-CRAN-rsample >= 1.1.0 BuildRequires: R-CRAN-recipes >= 1.0.0 BuildRequires: R-CRAN-dials >= 0.0.4 BuildRequires: R-CRAN-abind BuildRequires: R-CRAN-foreach BuildRequires: R-CRAN-kernlab BuildRequires: R-CRAN-magrittr BuildRequires: R-methods BuildRequires: R-CRAN-nnet BuildRequires: R-CRAN-party BuildRequires: R-CRAN-polspline BuildRequires: R-CRAN-progress BuildRequires: R-CRAN-rlang BuildRequires: R-CRAN-Rsolnp BuildRequires: R-CRAN-survival BuildRequires: R-CRAN-tibble BuildRequires: R-utils Requires: R-CRAN-ggplot2 >= 3.4.0 Requires: R-CRAN-cli >= 3.1.0 Requires: R-CRAN-Matrix >= 1.5.0 Requires: R-CRAN-rsample >= 1.1.0 Requires: R-CRAN-recipes >= 1.0.0 Requires: R-CRAN-dials >= 0.0.4 Requires: R-CRAN-abind Requires: R-CRAN-foreach Requires: R-CRAN-kernlab Requires: R-CRAN-magrittr Requires: R-methods Requires: R-CRAN-nnet Requires: R-CRAN-party Requires: R-CRAN-polspline Requires: R-CRAN-progress Requires: R-CRAN-rlang Requires: R-CRAN-Rsolnp Requires: R-CRAN-survival Requires: R-CRAN-tibble Requires: R-utils %description Meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Approaches for model fitting and prediction of numerical, categorical, or censored time-to-event outcomes include traditional regression models, regularization methods, tree-based methods, support vector machines, neural networks, ensembles, data preprocessing, filtering, and model tuning and selection. Performance metrics are provided for model assessment and can be estimated with independent test sets, split sampling, cross-validation, or bootstrap resampling. Resample estimation can be executed in parallel for faster processing and nested in cases of model tuning and selection. Modeling results can be summarized with descriptive statistics; calibration curves; variable importance; partial dependence plots; confusion matrices; and ROC, lift, and other performance curves. %prep %setup -q -c -n %{packname} # fix end of executable files find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \; # prevent binary stripping [ -d %{packname}/src ] && find %{packname}/src -type f -exec \ sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true [ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \ sed -i 's@-g0@@g' {} \; || true # don't allow local prefix in executable scripts find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \; %build %install mkdir -p %{buildroot}%{rlibdir} %{_bindir}/R CMD INSTALL -l %{buildroot}%{rlibdir} %{packname} test -d %{packname}/src && (cd %{packname}/src; rm -f *.o *.so) rm -f %{buildroot}%{rlibdir}/R.css # remove buildroot from installed files find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \; %files %{rlibdir}/%{packname}