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Authors
William D. McGinnis (0000-0002-3009-9465), Chapman Siu (0000-0002-2089-3796), Andre Silva (0000-0001-5104-0465), Hanyu Huang (0000-0001-8503-1014), Jan Motl (0000-0002-0388-3190), Kaspar Paul Westenthanner (0009-0007-4284-3953), Jonathan Castaldo (0009-0001-2553-5920)
Citation
McGinnis et al., (2026). Category Encoders: a scikit-learn-contrib package of transformers for encoding categorical data. Journal of Open Source Software, 11(124), 10645, https://doi.org/10.21105/joss.10645
@article{McGinnis2026,
doi = {10.21105/joss.10645},
url = {https://doi.org/10.21105/joss.10645},
year = {2026},
publisher = {The Open Journal},
volume = {11},
number = {124},
pages = {10645},
author = {McGinnis, William D. and Siu, Chapman and Silva, Andre and Huang, Hanyu and Motl, Jan and Westenthanner, Kaspar Paul and Castaldo, Jonathan},
title = {Category Encoders: a scikit-learn-contrib package of transformers for encoding categorical data},
journal = {Journal of Open Source Software}
}
Tags
machine learning python scikit-learn
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This work is licensed under a Creative Commons Attribution 4.0 International License.
