Package: automl 1.3.2

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.

Authors:Alex Boulangé [aut, cre]

automl_1.3.2.tar.gz
automl_1.3.2.zip(r-4.5)automl_1.3.2.zip(r-4.4)automl_1.3.2.zip(r-4.3)
automl_1.3.2.tgz(r-4.4-any)automl_1.3.2.tgz(r-4.3-any)
automl_1.3.2.tar.gz(r-4.5-noble)automl_1.3.2.tar.gz(r-4.4-noble)
automl_1.3.2.tgz(r-4.4-emscripten)automl_1.3.2.tgz(r-4.3-emscripten)
automl.pdf |automl.html✨
automl/json (API)
NEWS

# Install 'automl' in R:
install.packages('automl', repos = c('https://aboulaboul.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/aboulaboul/automl/issues

On CRAN:

3 exports 28 stars 2.36 score 0 dependencies 29 scripts 384 downloads

Last updated 5 years agofrom:55b1ad7285. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-winOKSep 07 2024
R-4.5-linuxOKSep 07 2024
R-4.4-winOKSep 07 2024
R-4.4-macOKSep 07 2024
R-4.3-winOKSep 07 2024
R-4.3-macOKSep 07 2024

Exports:automl_predictautoml_trainautoml_train_manual

Dependencies:

howto_automl.pdf

Rendered fromhowto_automl.Rnwusingutils::Sweaveon Sep 07 2024.

Last update: 2019-09-11
Started: 2018-10-21