File R-GMDH2.spec of Package R-GMDH2

# Automatically generated by CRAN2OBS
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# Spec file for package GMDH2 
# This file is auto-generated using information in the package source, 
# esp. Description and Summary. Improvements in that area should be 
# discussed with upstream. 
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%global packname  GMDH2 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.8 
Release:        0 
Summary:        Binary Classification via GMDH-Type Neural Network Algorithms 
Group:          Development/Libraries/Other 
License:        GPL (>= 2) 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         GMDH2_1.8.tar.gz 
Requires:       R-base 
Requires:	R-e1071
Requires:	R-randomForest
Requires:	R-glmnet
Requires:	R-plotly
Requires:	R-magrittr
Requires:	R-xtable
Requires:	R-proxy
Requires:	R-foreach
Requires:	R-shape
Requires:	R-Rcpp
Requires:	R-RcppEigen
Requires:	R-ggplot2
Requires:	R-scales
Requires:	R-httr
Requires:	R-jsonlite
Requires:	R-digest
Requires:	R-viridisLite
Requires:	R-base64enc
Requires:	R-htmltools
Requires:	R-htmlwidgets
Requires:	R-tidyr
Requires:	R-RColorBrewer
Requires:	R-dplyr
Requires:	R-vctrs
Requires:	R-tibble
Requires:	R-lazyeval
Requires:	R-rlang
Requires:	R-crosstalk
Requires:	R-purrr
Requires:	R-data.table
Requires:	R-promises
Requires:	R-R6
Requires:	R-cli
Requires:	R-generics
Requires:	R-glue
Requires:	R-lifecycle
Requires:	R-pillar
Requires:	R-tidyselect
Requires:	R-iterators
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-withr
Requires:	R-fastmap
Requires:	R-knitr
Requires:	R-rmarkdown
Requires:	R-yaml
Requires:	R-curl
Requires:	R-mime
Requires:	R-openssl
Requires:	R-later
Requires:	R-farver
Requires:	R-labeling
Requires:	R-munsell
Requires:	R-fansi
Requires:	R-pkgconfig
Requires:	R-stringr
Requires:	R-cpp11
Requires:	R-evaluate
Requires:	R-highr
Requires:	R-xfun
Requires:	R-colorspace
Requires:	R-askpass
Requires:	R-utf8
Requires:	R-bslib
Requires:	R-fontawesome
Requires:	R-jquerylib
Requires:	R-tinytex
Requires:	R-stringi
Requires:	R-sys
Requires:	R-cachem
Requires:	R-memoise
Requires:	R-sass
Requires:	R-fs
Requires:	R-rappdirs
 
# %%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-randomForest
BuildRequires: 	R-glmnet
BuildRequires: 	R-plotly
BuildRequires: 	R-magrittr
BuildRequires: 	R-xtable
BuildRequires: 	R-proxy
BuildRequires: 	R-foreach
BuildRequires: 	R-shape
BuildRequires: 	R-Rcpp-devel
BuildRequires: 	R-RcppEigen-devel
BuildRequires: 	R-ggplot2
BuildRequires: 	R-scales
BuildRequires: 	R-httr
BuildRequires: 	R-jsonlite
BuildRequires: 	R-digest
BuildRequires: 	R-viridisLite
BuildRequires: 	R-base64enc
BuildRequires: 	R-htmltools
BuildRequires: 	R-htmlwidgets
BuildRequires: 	R-tidyr
BuildRequires: 	R-RColorBrewer
BuildRequires: 	R-dplyr
BuildRequires: 	R-vctrs
BuildRequires: 	R-tibble
BuildRequires: 	R-lazyeval
BuildRequires: 	R-rlang
BuildRequires: 	R-crosstalk
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BuildRequires: 	R-cachem
BuildRequires: 	R-memoise
BuildRequires: 	R-sass
BuildRequires: 	R-fs
BuildRequires: 	R-rappdirs
 
Suggests:	R-mlbench
%description 
Performs binary classification via Group Method of Data Handling (GMDH) 
- type neural network algorithms. There exist two main algorithms 
available in GMDH() and dceGMDH() functions. GMDH() performs 
classification via GMDH algorithm for a binary response and returns 
important variables. dceGMDH() performs classification via diverse 
classifiers ensemble based on GMDH (dce-GMDH) algorithm. Also, the 
package produces a well-formatted table of descriptives for a binary 
response. Moreover, it produces confusion matrix, its related 
statistics and scatter plot (2D and 3D) with classification labels of 
binary classes to assess the prediction performance. All 'GMDH2' 
functions are designed for a binary response (Dag et al., 2019, 
<https://download.atlantis-press.com/article/125911202.pdf>). 
 
%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
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/citation
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog