fastml: Fast Machine Learning Model Training and Evaluation

Streamlines the training, evaluation, and comparison of multiple machine learning models with minimal code by providing comprehensive data preprocessing and support for a wide range of algorithms with hyperparameter tuning. It offers performance metrics and visualization tools to facilitate efficient and effective machine learning workflows.

Version: 0.2.0
Imports: recipes, dplyr, ggplot2, reshape2, foreach, doParallel, rsample, parsnip, tune, workflows, yardstick, tibble, rlang, stats, dials, magrittr
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, C50, glmnet, xgboost, ranger, crayon, kernlab, discrim, baguette, plsmod, keras, lightgbm, bonsai, rstanarm
Published: 2024-11-30
DOI: 10.32614/CRAN.package.fastml
Author: Selcuk Korkmaz ORCID iD [aut, cre], Dincer Goksuluk ORCID iD [aut]
Maintainer: Selcuk Korkmaz <selcukorkmaz at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
CRAN checks: fastml results

Documentation:

Reference manual: fastml.pdf

Downloads:

Package source: fastml_0.2.0.tar.gz
Windows binaries: r-devel: fastml_0.1.0.zip, r-release: fastml_0.2.0.zip, r-oldrel: fastml_0.2.0.zip
macOS binaries: r-release (arm64): fastml_0.2.0.tgz, r-oldrel (arm64): fastml_0.2.0.tgz, r-release (x86_64): fastml_0.2.0.tgz, r-oldrel (x86_64): fastml_0.2.0.tgz
Old sources: fastml archive

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