File R-metaSVR.spec of Package R-metaSVR
# Automatically generated by CRAN2OBS
#
# Spec file for package metaSVR
# This file is auto-generated using information in the package source,
# esp. Description and Summary. Improvements in that area should be
# discussed with upstream.
#
# Copyright (c) 2025 SUSE LINUX GmbH, Nuernberg, Germany.
#
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# remain the property of their copyright owners, unless otherwise agreed
# upon. The license for this file, and modifications and additions to the
# file, is the same license as for the pristine package itself (unless the
# license for the pristine package is not an Open Source License, in which
# case the license is the MIT License). An "Open Source License" is a
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%global packname metaSVR
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 0.1.0
Release: 0
Summary: Support Vector Regression with Metaheuristic Algorithms Optimization
Group: Development/Libraries/Other
License: GPL (>= 3)
URL: http://cran.r-project.org/web/packages/%{packname}
Source: metaSVR_0.1.0.tar.gz
Requires: R-base
Requires: R-e1071
Requires: R-hms
Requires: R-proxy
Requires: R-cli
Requires: R-lifecycle
Requires: R-pkgconfig
Requires: R-rlang
Requires: R-vctrs
Requires: R-glue
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse}
# # Three others commonly needed
# BuildRequires: tex(ae.sty)
# BuildRequires: tex(fancyvrb.sty)
# BuildRequires: tex(inconsolata.sty)
# BuildRequires: tex(natbib.sty)
# %else
# BuildRequires: texlive
# %endif
# BuildRequires: texinfo
BuildRequires: fdupes
BuildRequires: R-base
BuildRequires: R-e1071
BuildRequires: R-hms
BuildRequires: R-proxy
BuildRequires: R-cli
BuildRequires: R-lifecycle
BuildRequires: R-pkgconfig
BuildRequires: R-rlang
BuildRequires: R-vctrs
BuildRequires: R-glue
Suggests: R-testthat
%description
Provides a hybrid modeling framework combining Support Vector
Regression (SVR) with metaheuristic optimization algorithms, including
the Archimedes Optimization Algorithm (AO) (Hashim et al. (2021)
<doi:10.1007/s10489-020-01893-z>), Coot Bird Optimization (CBO) (Naruei
& Keynia (2021) <doi:10.1016/j.eswa.2021.115352>), and their hybrid
(AOCBO), as well as several others such as Harris Hawks Optimization
(HHO) (Heidari et al. (2019) <doi:10.1016/j.future.2019.02.028>), Gray
Wolf Optimizer (GWO) (Mirjalili et al. (2014)
<doi:10.1016/j.advengsoft.2013.12.007>), Ant Lion Optimization (ALO)
(Mirjalili (2015) <doi:10.1016/j.advengsoft.2015.01.010>), and Enhanced
Harris Hawk Optimization with Coot Bird Optimization (EHHOCBO) (Cui et
al. (2023) <doi:10.32604/cmes.2023.026019>). The package enables
automatic tuning of SVR hyperparameters (cost, gamma, and epsilon) to
enhance prediction performance. Suitable for regression tasks in
domains such as renewable energy forecasting and hourly data
prediction. For more details about implementation and parameter bounds
see: Setiawan et al. (2021) <doi:10.1016/j.procs.2020.12.003> and Liu
et al. (2018) <doi:10.1155/2018/6076475>.
%prep
%setup -q -c -n %{packname}
# the next line is needed, because we build without --clean in between two packages
rm -rf ~/.R
%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
%fdupes -s %{buildroot}%{rlibdir}
#%%check
#%%{_bindir}/R CMD check %%{packname}
%files
%dir %{rlibdir}/%{packname}
%{rlibdir}/%{packname}/CITATION
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%changelog
