evoFE
0.1.0Evolutionary Feature Engineering
Overview
Automates feature engineering using evolutionary algorithms inspired by genetic programming. Starting from raw input features, the package evolves candidate transformation recipes through selection, crossover, and mutation, evaluating fitness via cross-validation or train/validation splits with gradient-boosted tree models ('LightGBM' or 'XGBoost'). Built-in transformers include arithmetic, logarithmic, and power operations, interaction terms, target encoding, quantile and log-based binning, principal component analysis, truncated singular value decomposition, Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction, and minimum spanning tree (MST) graph-based clustering. The evolutionary search yields an optimised feature recipe that can be applied to new data for prediction. Methods are described in McInnes et al. (2018) doi:10.21105/joss.00861, Ke et al. (2017) https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-framework, Chen and Guestrin (2016) doi:10.1145/2939672.2939785, Gagolewski (2021) doi:10.1016/j.softx.2021.100722, Gagolewski (2026) doi:10.32614/CRAN.package.lumbermark, and Gagolewski (2026) doi:10.32614/CRAN.package.deadwood.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-108 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- not tracked
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- 0.1.0Latest2026-06-09 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-06-09
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 61 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("evoFE")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.