NNbenchmark: Datasets and Functions to Benchmark Neural Network Packages

Datasets and functions to benchmark (convergence, speed, ease of use) R packages dedicated to regression with neural networks (no classification in this version). The templates for the tested packages are available in the R, R Markdown and HTML formats at <https://github.com/pkR-pkR/NNbenchmarkTemplates> and <https://theairbend3r.github.io/NNbenchmarkWeb/index.html>. The submitted article to the R-Journal can be read at <https://www.inmodelia.com/gsoc2020.html>.

Version: 3.2.0
Depends: R (≥ 3.5.0)
Imports: R6, pkgload
Suggests: brnn, validann
Published: 2021-06-05
Author: Patrice Kiener ORCID iD [aut, cre], Christophe Dutang ORCID iD [aut], Salsabila Mahdi ORCID iD [aut], Akshaj Verma ORCID iD [aut], Yifu Yan [ctb]
Maintainer: Patrice Kiener <rpackages at inmodelia.com>
License: GPL-2
URL: https://github.com/pkR-pkR/NNbenchmark
NeedsCompilation: no
Materials: README NEWS
CRAN checks: NNbenchmark results

Documentation:

Reference manual: NNbenchmark.pdf

Downloads:

Package source: NNbenchmark_3.2.0.tar.gz
Windows binaries: r-devel: NNbenchmark_3.2.0.zip, r-release: NNbenchmark_3.2.0.zip, r-oldrel: NNbenchmark_3.2.0.zip
macOS binaries: r-release (arm64): NNbenchmark_3.2.0.tgz, r-oldrel (arm64): NNbenchmark_3.2.0.tgz, r-release (x86_64): NNbenchmark_3.2.0.tgz
Old sources: NNbenchmark archive

Linking:

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