automl: Deep Learning with Metaheuristic

Fits from simple regression to highly customizable deep neural networks either with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost function. A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization.

Version: 1.3.2
Imports: stats, utils, parallel
Suggests: datasets
Published: 2020-01-16
Author: Alex Boulangé [aut, cre]
Maintainer: Alex Boulangé <aboul at free.fr>
BugReports: https://github.com/aboulaboul/automl/issues
License: GPL-2 | GPL-3 [expanded from: GNU General Public License]
URL: https://aboulaboul.github.io/automl https://github.com/aboulaboul/automl
NeedsCompilation: no
Materials: README NEWS
CRAN checks: automl results

Documentation:

Reference manual: automl.pdf
Vignettes: howto_automl.pdf

Downloads:

Package source: automl_1.3.2.tar.gz
Windows binaries: r-devel: automl_1.3.2.zip, r-release: automl_1.3.2.zip, r-oldrel: automl_1.3.2.zip
macOS binaries: r-release (arm64): automl_1.3.2.tgz, r-oldrel (arm64): automl_1.3.2.tgz, r-release (x86_64): automl_1.3.2.tgz
Old sources: automl archive

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