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densemlp: Dense Neural Networks for Tabular Classification and Regression

Provides dense feed-forward neural network models for tabular regression and classification using 'torch'. The package supports modern extensions around dense neural network blocks, including dropout, batch normalization, residual connections, gated blocks, and optional input projection.

Version: 0.5.0
Imports: ggplot2, stats, torch
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-08-08
DOI: 10.32614/CRAN.package.densemlp
Author: Imad EL BADISY [aut, cre]
Maintainer: Imad EL BADISY <elbadisyimad at gmail.com>
BugReports: https://github.com/ielbadisy/densemlp/issues
License: MIT + file LICENSE
URL: https://github.com/ielbadisy/densemlp
NeedsCompilation: no
Materials: README
CRAN checks: densemlp results

Documentation:

Reference manual: densemlp.html , densemlp.pdf
Vignettes: Getting Started with densemlp (source, R code)

Downloads:

Package source: densemlp_0.5.0.tar.gz
Windows binaries: r-devel: not available, r-release: densemlp_0.5.0.zip, r-oldrel: densemlp_0.5.0.zip
macOS binaries: r-release (arm64): densemlp_0.5.0.tgz, r-oldrel (arm64): densemlp_0.5.0.tgz, r-release (x86_64): densemlp_0.5.0.tgz, r-oldrel (x86_64): densemlp_0.5.0.tgz

Linking:

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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.
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