File R-daltoolbox.spec of Package R-daltoolbox
# Automatically generated by CRAN2OBS
#
# Spec file for package daltoolbox
# 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) 2026 SUSE LINUX GmbH, Nuernberg, Germany.
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# Please submit bugfixes or comments via http://bugs.opensuse.org/
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%global packname daltoolbox
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 1.3.727
Release: 0
Summary: Leveraging Experiment Lines to Data Analytics
Group: Development/Libraries/Other
License: MIT + file LICENSE
URL: http://cran.r-project.org/web/packages/%{packname}
Source: daltoolbox_1.3.727.tar.gz
Requires: R-base
Requires: R-FNN
Requires: R-caret
Requires: R-arules
Requires: R-arulesSequences
Requires: R-dbscan
Requires: R-dplyr
Requires: R-e1071
Requires: R-ggplot2
Requires: R-mclust
Requires: R-randomForest
Requires: R-reshape
Requires: R-tree
Requires: R-generics
Requires: R-foreach
Requires: R-ModelMetrics
Requires: R-plyr
Requires: R-pROC
Requires: R-recipes
Requires: R-reshape2
Requires: R-withr
Requires: R-Rcpp
Requires: R-cli
Requires: R-glue
Requires: R-lifecycle
Requires: R-magrittr
Requires: R-pillar
Requires: R-R6
Requires: R-rlang
Requires: R-tibble
Requires: R-tidyselect
Requires: R-vctrs
Requires: R-proxy
Requires: R-gtable
Requires: R-isoband
Requires: R-S7
Requires: R-scales
Requires: R-iterators
Requires: R-cpp11
Requires: R-data.table
Requires: R-utf8
Requires: R-clock
Requires: R-gower
Requires: R-hardhat
Requires: R-ipred
Requires: R-lubridate
Requires: R-purrr
Requires: R-sparsevctrs
Requires: R-tidyr
Requires: R-timeDate
Requires: R-stringr
Requires: R-farver
Requires: R-labeling
Requires: R-RColorBrewer
Requires: R-viridisLite
Requires: R-pkgconfig
Requires: R-tzdb
Requires: R-prodlim
Requires: R-timechange
Requires: R-stringi
Requires: R-diagram
Requires: R-lava
Requires: R-shape
Requires: R-future.apply
Requires: R-numDeriv
Requires: R-progressr
Requires: R-SQUAREM
Requires: R-future
Requires: R-globals
Requires: R-digest
Requires: R-listenv
Requires: R-parallelly
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse}
# # Three others commonly needed
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# %else
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# %endif
# BuildRequires: texinfo
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BuildRequires: R-arules
BuildRequires: R-arulesSequences
BuildRequires: R-dbscan
BuildRequires: R-dplyr
BuildRequires: R-e1071
BuildRequires: R-ggplot2
BuildRequires: R-mclust
BuildRequires: R-randomForest
BuildRequires: R-reshape
BuildRequires: R-tree
BuildRequires: R-generics
BuildRequires: R-foreach
BuildRequires: R-ModelMetrics
BuildRequires: R-plyr
BuildRequires: R-pROC
BuildRequires: R-recipes
BuildRequires: R-reshape2
BuildRequires: R-withr
BuildRequires: R-Rcpp-devel
BuildRequires: R-cli
BuildRequires: R-glue
BuildRequires: R-lifecycle
BuildRequires: R-magrittr
BuildRequires: R-pillar
BuildRequires: R-R6
BuildRequires: R-rlang
BuildRequires: R-tibble
BuildRequires: R-tidyselect
BuildRequires: R-vctrs
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BuildRequires: R-data.table
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BuildRequires: R-SQUAREM
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Suggests: R-adabag
Suggests: R-glmnet
Suggests: R-leaps
Suggests: R-ipred
Suggests: R-xgboost
Suggests: R-arulesViz
Suggests: R-GGally
Suggests: R-igraph
%description
The natural increase in the complexity of current research experiments
and data demands better tools to enhance productivity in Data
Analytics. The package is a framework designed to address the modern
challenges in data analytics workflows. The package is inspired by
Experiment Line concepts. It aims to provide seamless support for users
in developing their data mining workflows by offering a uniform data
model and method API. It enables the integration of various data mining
activities, including data preprocessing, classification, regression,
clustering, and time series prediction. It also offers options for
hyper-parameter tuning and supports integration with existing libraries
and languages. Overall, the package provides researchers with a
comprehensive set of functionalities for data science, promoting ease
of use, extensibility, and integration with various tools and
libraries. Information on Experiment Line is based on Ogasawara et al.
(2009) <doi:10.1007/978-3-642-02279-1_20>.
%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}
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%license %{rlibdir}/%{packname}/LICENSE
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/logo.png
%{rlibdir}/%{packname}/logo.pptx
%changelog
