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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "tidylearn" in publications use:'
type: software
license: MIT
title: 'tidylearn: A Unified Tidy Interface to R''s Machine Learning Ecosystem'
version: 0.3.1.9000
identifiers:
- type: doi
  value: 10.32614/CRAN.package.tidylearn
abstract: 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) <https://doi.org/10.1023/A:1010933404324>,
  LASSO regression Tibshirani (1996) <https://doi.org/10.1111/j.2517-6161.1996.tb02080.x>,
  elastic net Zou and Hastie (2005) <https://doi.org/10.1111/j.1467-9868.2005.00503.x>,
  support vector machines Cortes and Vapnik (1995) <https://doi.org/10.1007/BF00994018>,
  and gradient boosting Friedman (2001) <https://doi.org/10.1214/aos/1013203451>.
authors:
- family-names: Tobias
  given-names: Cesaire
  email: cesaire@sheetsolved.com
preferred-citation:
  type: manual
  title: 'tidylearn: A Unified Tidy Interface to R''s Machine Learning Ecosystem'
  authors:
  - family-names: Tobias
    given-names: Cesaire
    email: cesaire@sheetsolved.com
  year: '2025'
  url: https://github.com/ces0491/tidylearn
repository: https://ces0491.r-universe.dev
repository-code: https://github.com/ces0491/tidylearn
commit: f36a03ed8af1e8d9c46e66c946a7524832ad23c3
url: https://github.com/ces0491/tidylearn
date-released: '2026-05-22'
contact:
- family-names: Tobias
  given-names: Cesaire
  email: cesaire@sheetsolved.com