%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  NumericEnsembles
%global packver   0.8.0
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          0.8.0
Release:          1%{?dist}%{?buildtag}
Summary:          Automatically Runs 23 Individual and 17 Ensembles of Models

License:          MIT + file LICENSE
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 4.1.0
Requires:         R-core >= 4.1.0
BuildArch:        noarch
BuildRequires:    R-CRAN-Cubist 
BuildRequires:    R-CRAN-Metrics 
BuildRequires:    R-CRAN-arm 
BuildRequires:    R-CRAN-brnn 
BuildRequires:    R-CRAN-broom 
BuildRequires:    R-CRAN-car 
BuildRequires:    R-CRAN-caret 
BuildRequires:    R-CRAN-corrplot 
BuildRequires:    R-CRAN-doParallel 
BuildRequires:    R-CRAN-dplyr 
BuildRequires:    R-CRAN-e1071 
BuildRequires:    R-CRAN-earth 
BuildRequires:    R-CRAN-gam 
BuildRequires:    R-CRAN-gbm 
BuildRequires:    R-CRAN-ggplot2 
BuildRequires:    R-CRAN-glmnet 
BuildRequires:    R-graphics 
BuildRequires:    R-grDevices 
BuildRequires:    R-CRAN-gridExtra 
BuildRequires:    R-CRAN-ipred 
BuildRequires:    R-CRAN-leaps 
BuildRequires:    R-CRAN-nnet 
BuildRequires:    R-parallel 
BuildRequires:    R-CRAN-pls 
BuildRequires:    R-CRAN-purrr 
BuildRequires:    R-CRAN-randomForest 
BuildRequires:    R-CRAN-reactable 
BuildRequires:    R-CRAN-reactablefmtr 
BuildRequires:    R-CRAN-readr 
BuildRequires:    R-CRAN-rpart 
BuildRequires:    R-stats 
BuildRequires:    R-CRAN-tidyr 
BuildRequires:    R-CRAN-tree 
BuildRequires:    R-utils 
BuildRequires:    R-CRAN-xgboost 
Requires:         R-CRAN-Cubist 
Requires:         R-CRAN-Metrics 
Requires:         R-CRAN-arm 
Requires:         R-CRAN-brnn 
Requires:         R-CRAN-broom 
Requires:         R-CRAN-car 
Requires:         R-CRAN-caret 
Requires:         R-CRAN-corrplot 
Requires:         R-CRAN-doParallel 
Requires:         R-CRAN-dplyr 
Requires:         R-CRAN-e1071 
Requires:         R-CRAN-earth 
Requires:         R-CRAN-gam 
Requires:         R-CRAN-gbm 
Requires:         R-CRAN-ggplot2 
Requires:         R-CRAN-glmnet 
Requires:         R-graphics 
Requires:         R-grDevices 
Requires:         R-CRAN-gridExtra 
Requires:         R-CRAN-ipred 
Requires:         R-CRAN-leaps 
Requires:         R-CRAN-nnet 
Requires:         R-parallel 
Requires:         R-CRAN-pls 
Requires:         R-CRAN-purrr 
Requires:         R-CRAN-randomForest 
Requires:         R-CRAN-reactable 
Requires:         R-CRAN-reactablefmtr 
Requires:         R-CRAN-readr 
Requires:         R-CRAN-rpart 
Requires:         R-stats 
Requires:         R-CRAN-tidyr 
Requires:         R-CRAN-tree 
Requires:         R-utils 
Requires:         R-CRAN-xgboost 

%description
Automatically runs 23 individual models and 17 ensembles on numeric data.
The package automatically returns complete results on all 40 models, 25
charts, multiple tables. The user simply provides the data, and answers a
few questions (for example, how many times would you like to resample the
data). From there the package randomly splits the data into train, test
and validation sets, builds models on the training data, makes predictions
on the test and validation sets, measures root mean squared error (RMSE),
removes features above a user-set level of Variance Inflation Factor, and
has several optional features including scaling all numeric data, four
different ways to handle strings in the data. Perhaps the most significant
feature is the package's ability to make predictions using the 40 pre
trained models on totally new (untrained) data if the user selects that
feature. This feature alone represents a very effective solution to the
issue of reproducibility of models in data science. The package can also
randomly resample the data as many times as the user sets, thus giving
more accurate results than a single run. The graphs provide many results
that are not typically found. For example, the package automatically
calculates the Kolmogorov-Smirnov test for each of the 40 models and plots
a bar chart of the results, a bias bar chart of each of the 40 models, as
well as several plots for exploratory data analysis (automatic histograms
of the numeric data, automatic histograms of the numeric data). The
package also automatically creates a summary report that can be both
sorted and searched for each of the 40 models, including RMSE, bias, train
RMSE, test RMSE, validation RMSE, overfitting and duration. The best
results on the holdout data typically beat the best results in data
science competitions and published results for the same data set.

%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}