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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 |
DOI: | 10.32614/CRAN.package.NNbenchmark |
Author: | Patrice Kiener |
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 |
Reference manual: | NNbenchmark.pdf |
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, r-oldrel (x86_64): NNbenchmark_3.2.0.tgz |
Old sources: | NNbenchmark archive |
Please use the canonical form https://CRAN.R-project.org/package=NNbenchmark to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.