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: |
0.4.0 |
| 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 |
| Suggests: |
testthat (≥ 3.0.0), C50, glmnet, xgboost, ranger, crayon, kernlab, klaR, kknn, keras, lightgbm, rstanarm, mixOmics |
| Published: |
2025-01-08 |
| DOI: |
10.32614/CRAN.package.fastml |
| Author: |
Selcuk Korkmaz 
[aut, cre],
Dincer Goksuluk
[aut],
Eda Karaismailoglu
[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:
Downloads:
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