tidylearn
0.4.0A Unified Tidy Interface to R's Machine Learning Ecosystem
Overview
Provides a unified tidyverse-compatible interface to R's machine learning ecosystem - from data ingestion to model publishing. The tl_read() family reads data from files ('CSV', 'Excel', 'Parquet', 'JSON'), databases ('SQLite', 'PostgreSQL', 'MySQL', 'BigQuery'), and cloud sources ('S3', 'GitHub', 'Kaggle'). The tl_model() function wraps established implementations from 'glmnet', 'randomForest', 'xgboost', 'e1071', 'rpart', 'gbm', 'nnet', 'cluster', 'dbscan', and others with consistent function signatures and tidy tibble output. Results flow into unified 'ggplot2'-based visualization and optional formatted 'gt' tables via the tl_table() family. 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.
Install
Health
- OK2026-08-0413 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-1414 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- ERROR2026-04-1013 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 7%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Repository
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Repository practices
5 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/ces0491/tidylearn on 2026-08-16.
Development tooling
Uses AI-assisted development tooling (declared in repo)
Earliest detected marker: claude on 2026-01-19
Most recent: claude on 2026-01-19
- claude: on 2026-01-19 · evidence B, D
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
6 releases. Pick two to compare their code metrics. R releases are shown for context.
Package metadata
- First published
- 2026-02-06
- Total releases
- 6 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.6.0
- Download size
- 641 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("tidylearn")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.