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evoFE  

Evolutionary Feature Engineering
View on CRAN: Click here


Download and install evoFE package within the R console
Install from CRAN:
install.packages("evoFE")

Install from Github:
library("remotes")
install_github("cran/evoFE")

Install by package version:
library("remotes")
install_version("evoFE", "0.1.0")



Attach the package and use:
library("evoFE")
Maintained by
Gustavo Pereira
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-09
Latest Update: 2026-06-09
Description:
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>.
How to cite:
Gustavo Pereira (2026). evoFE: Evolutionary Feature Engineering. R package version 0.1.0, https://cran.r-project.org/web/packages/evoFE. Accessed 27 Jun. 2026.
Previous versions and publish date:
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Complete documentation for evoFE
Functions, R codes and Examples using the evoFE R package
Full evoFE package functions and examples
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