tidylearn
A Unified Tidy Interface to R's Machine Learning Ecosystem
Provides a unified tidyverse-compatible interface to R's machine learning packages. Wraps established implementations from 'glmnet', 'randomForest', 'xgboost', 'e1071', 'rpart', 'gbm', 'nnet', 'cluster', 'dbscan', and others - providing consistent function signatures, tidy tibble output, unified 'ggplot2'-based visualization, and optional formatted 'gt' tables via the tl_table() family of functions. The underlying algorithms are unchanged; 'tidylearn' simply makes them easier to use together. Access raw model objects via the $fit slot for package-specific functionality. Methods include random forests Breiman (2001) <doi:10.1023/A:1010933404324>, LASSO regression Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, elastic net Zou and Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, support vector machines Cortes and Vapnik (1995) <doi:10.1007/BF00994018>, and gradient boosting Friedman (2001) <doi:10.1214/aos/1013203451>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.3.0 |
rolling linux/jammy R-4.5 | tidylearn_0.3.0.tar.gz |
2.0 MiB |
0.3.0 |
rolling linux/noble R-4.5 | tidylearn_0.3.0.tar.gz |
2.0 MiB |
0.3.0 |
rolling source/ R- | tidylearn_0.3.0.tar.gz |
1.4 MiB |
0.3.0 |
latest linux/jammy R-4.5 | tidylearn_0.3.0.tar.gz |
2.0 MiB |
0.3.0 |
latest linux/noble R-4.5 | tidylearn_0.3.0.tar.gz |
2.0 MiB |
0.3.0 |
latest source/ R- | tidylearn_0.3.0.tar.gz |
1.4 MiB |
0.3.0 |
2026-04-26 source/ R- | tidylearn_0.3.0.tar.gz |
1.4 MiB |
0.3.0 |
2026-04-23 source/ R- | tidylearn_0.3.0.tar.gz |
1.4 MiB |
0.2.0 |
2026-04-09 windows/windows R-4.5 | tidylearn_0.2.0.zip |
1.9 MiB |