%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname funcml %global packver 0.9.0 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.9.0 Release: 1%{?dist}%{?buildtag} Summary: Functional Machine Learning Framework License: GPL-3 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.5.0 Requires: R-core >= 3.5.0 BuildArch: noarch BuildRequires: R-stats BuildRequires: R-utils BuildRequires: R-CRAN-ggplot2 BuildRequires: R-CRAN-functionals BuildRequires: R-grDevices BuildRequires: R-tools BuildRequires: R-CRAN-data.table BuildRequires: R-CRAN-MASS BuildRequires: R-CRAN-mgcv BuildRequires: R-CRAN-nnet BuildRequires: R-CRAN-rpart BuildRequires: R-CRAN-glmnet BuildRequires: R-CRAN-ranger BuildRequires: R-CRAN-e1071 BuildRequires: R-CRAN-randomForest BuildRequires: R-CRAN-gbm BuildRequires: R-CRAN-C50 BuildRequires: R-CRAN-kknn BuildRequires: R-CRAN-earth BuildRequires: R-CRAN-naivebayes BuildRequires: R-CRAN-mda BuildRequires: R-CRAN-ada BuildRequires: R-CRAN-pls BuildRequires: R-CRAN-partykit BuildRequires: R-CRAN-dbarts BuildRequires: R-CRAN-torch BuildRequires: R-CRAN-xgboost BuildRequires: R-CRAN-lightgbm BuildRequires: R-CRAN-densemlp Requires: R-stats Requires: R-utils Requires: R-CRAN-ggplot2 Requires: R-CRAN-functionals Requires: R-grDevices Requires: R-tools Requires: R-CRAN-data.table Requires: R-CRAN-MASS Requires: R-CRAN-mgcv Requires: R-CRAN-nnet Requires: R-CRAN-rpart Requires: R-CRAN-glmnet Requires: R-CRAN-ranger Requires: R-CRAN-e1071 Requires: R-CRAN-randomForest Requires: R-CRAN-gbm Requires: R-CRAN-C50 Requires: R-CRAN-kknn Requires: R-CRAN-earth Requires: R-CRAN-naivebayes Requires: R-CRAN-mda Requires: R-CRAN-ada Requires: R-CRAN-pls Requires: R-CRAN-partykit Requires: R-CRAN-dbarts Requires: R-CRAN-torch Requires: R-CRAN-xgboost Requires: R-CRAN-lightgbm Requires: R-CRAN-densemlp %description A compact and explicit machine learning framework for supervised learning, resampling-based evaluation, hyperparameter tuning, learner comparison, interpretation, and plug-in g-computation. The package uses standard formulas for model specification and provides stable S3 interfaces for fitting, evaluation, tuning, interpretation, and causal estimation across a learner registry with multiple backend engines. Implemented interpretation methods build on established approaches such as permutation-based variable importance, partial dependence, individual conditional expectation, accumulated local effects, SHAP, and LIME; see Friedman (2001) , Goldstein et al. (2015) , Apley and Zhu (2020) , Lundberg and Lee (2017) , and Ribeiro et al. (2016) . The framework is intentionally opinionated: preprocessing is expected to occur outside the modeling step, and the API emphasizes explicit inputs, consistent object contracts, and compact interfaces rather than feature-by-feature competition with larger machine learning ecosystems. Plug-in g-computation follows Naimi, Cole, and Kennedy (2016) . %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}