File R-aifeducation.spec of Package R-aifeducation

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File R-aifeducation.spec of Package R-aifeducation

# Automatically generated by CRAN2OBS
# 
# Spec file for package aifeducation 
# 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) 2024 SUSE LINUX GmbH, Nuernberg, Germany. 
# 
# All modifications and additions to the file contributed by third parties 
# 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 
# license that conforms to the Open Source Definition (Version 1.9) 
# published by the Open Source Initiative. 
#  
# Please submit bugfixes or comments via http://bugs.opensuse.org/ 
# 
 
%global packname  aifeducation 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        0.3.3 
Release:        0 
Summary:        Artificial Intelligence for Education 
Group:          Development/Libraries/Other 
License:        GPL-3 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         aifeducation_0.3.3.tar.gz 
Requires:       R-base 
Requires:	R-abind
Requires:	R-foreach
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Requires:	R-iotarelr
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# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
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%description 
In social and educational settings, the use of Artificial Intelligence 
(AI) is a challenging task. Relevant data is often only available in 
handwritten forms, or the use of data is restricted by privacy 
policies. This often leads to small data sets. Furthermore, in the 
educational and social sciences, data is often unbalanced in terms of 
frequencies. To support educators as well as educational and social 
researchers in using the potentials of AI for their work, this package 
provides a unified interface for neural nets in 'keras', 'tensorflow', 
and 'pytorch' to deal with natural language problems. In addition, the 
package ships with a shiny app, providing a graphical user interface. 
This allows the usage of AI for people without skills in writing 
python/R scripts. The tools integrate existing mathematical and 
statistical methods for dealing with small data sets via 
pseudo-labeling (e.g. Lee (2013) 
<https://www.researchgate.net/publication/280581078_Pseudo-Label_The_Simple_and_Efficient_Semi-Supervised_Learning_Method_for_Deep_Neural_Networks>, 
Cascante-Bonilla et al. (2020) <doi:10.48550/arXiv.2001.06001>) and 
imbalanced data via the creation of synthetic cases (e.g. 
Bunkhumpornpat et al. (2012) <doi:10.1007/s10489-011-0287-y>). 
Performance evaluation of AI is connected to measures from content 
analysis which educational and social researchers are generally more 
familiar with (e.g. Berding & Pargmann (2022) <doi:10.30819/5581>, Gwet 
(2014) <ISBN:978-0-9708062-8-4>, Krippendorff (2019) 
<doi:10.4135/9781071878781>). Estimation of energy consumption and CO2 
emissions during model training is done with the 'python' library 
'codecarbon'.  Finally, all objects created with this package allow to 
share trained AI models with other people. 
 
%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
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/libs
%{rlibdir}/%{packname}/python
%{rlibdir}/%{packname}/
 
%changelog

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File R-aifeducation.spec of Package R-aifeducation

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