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: 0.6.1 Depends: R (≥ 3.5.0) Imports: recipes, dplyr, ggplot2, reshape2, rsample, parsnip, tune, workflows, yardstick, tibble, rlang, dials, RColorBrewer, baguette, bonsai, discrim, doFuture, finetune, future, plsmod, probably, viridisLite, DALEX, magrittr, patchwork, pROC, janitor, stringr, DT, GGally, UpSetR, VIM, broom, dbscan, ggpubr, gridExtra, htmlwidgets, kableExtra, moments, naniar, plotly, scales, skimr, tidyr, knitr, rmarkdown, purrr, mice, missForest Suggests: testthat (≥ 3.0.0), C50, glmnet, xgboost, ranger, crayon, kernlab, klaR, kknn, keras, lightgbm, rstanarm, mixOmics Published: 2025-06-10 DOI: 10.32614/CRAN.package.fastml Author: Selcuk Korkmaz [aut, cre], Dincer Goksuluk [aut], Eda Karaismailoglu [aut] Maintainer: Selcuk Korkmaz <selcukorkmaz at gmail.com> BugReports: https://github.com/selcukorkmaz/fastml/issues License: MIT + file LICENSE URL: https://github.com/selcukorkmaz/fastml NeedsCompilation: no Materials: README CRAN checks: fastml results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=fastml to link to this page.
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