%global __brp_check_rpaths %{nil} %global packname sboost %global packver 0.1.2 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.1.2 Release: 1%{?dist}%{?buildtag} Summary: Machine Learning with AdaBoost on Decision Stumps License: MIT + file LICENSE URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.4.0 Requires: R-core >= 3.4.0 BuildRequires: R-stats >= 3.4 BuildRequires: R-CRAN-dplyr >= 0.7.6 BuildRequires: R-CRAN-rlang >= 0.2.1 BuildRequires: R-CRAN-Rcpp >= 0.12.17 Requires: R-stats >= 3.4 Requires: R-CRAN-dplyr >= 0.7.6 Requires: R-CRAN-rlang >= 0.2.1 Requires: R-CRAN-Rcpp >= 0.12.17 %description Creates classifier for binary outcomes using Adaptive Boosting (AdaBoost) algorithm on decision stumps with a fast C++ implementation. For a description of AdaBoost, see Freund and Schapire (1997) . This type of classifier is nonlinear, but easy to interpret and visualize. Feature vectors may be a combination of continuous (numeric) and categorical (string, factor) elements. Methods for classifier assessment, predictions, and cross-validation also included. %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}