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: |
0.6.2 |
| 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: |
2025-07-24 |
| 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 |