%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname autoEnsemble %global packver 0.2 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.2 Release: 1%{?dist}%{?buildtag} Summary: Automated Stacked Ensemble Classifier for Severe Class Imbalance License: MIT + file LICENSE 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-CRAN-curl >= 4.3.0 BuildRequires: R-CRAN-h2o >= 3.34.0.0 BuildRequires: R-CRAN-h2otools >= 0.3 Requires: R-CRAN-curl >= 4.3.0 Requires: R-CRAN-h2o >= 3.34.0.0 Requires: R-CRAN-h2otools >= 0.3 %description An AutoML algorithm is developed to construct homogeneous or heterogeneous stacked ensemble models using specified base-learners. Various criteria are employed to identify optimal models, enhancing diversity among them and resulting in more robust stacked ensembles. The algorithm optimizes the model by incorporating an increasing number of top-performing models to create a diverse combination. Presently, only models from 'h2o.ai' are supported. %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}