fairGATE: Fair Gated Algorithm for Targeted Equity

Fairness-aware correction of a prediction model for binary and continuous outcomes with two or more protected groups and their intersections. A cross-fitted base learner (gradient-boosted trees or a neural network) is fitted without the protected attribute, and a gated mixture of neural experts learns a per-person correction to its score under a fairness penalty (a random-effects or variance penalty on outcome-stratified group means, or a thresholded worst-group penalty on error rates), with a cross-fitted disparity signal, an intervention cost, smoothed early stopping, a per-person export of adjustments with bootstrap stability intervals, and routing analyses of which expert corrects whom. Methods draw on mixture-of-experts neural networks by Jordan and Jacobs (1994) <doi:10.1007/978-1-4471-2097-1_113>, gradient boosting by Chen and Guestrin (2016) <doi:10.1145/2939672.2939785>, cross-fitting by Chernozhukov and co-authors (2018) <doi:10.1111/ectj.12097>, equalised odds by Hardt, Price and Srebro (2016) <doi:10.48550/arXiv.1610.02413>, the random-effects variance estimator of DerSimonian and Laird (1986) <doi:10.1016/0197-2456(86)90046-2>, and personalised treatment prediction for depression by Iniesta, Stahl and McGuffin (2016) <doi:10.1016/j.jpsychires.2016.03.016>.

Version:	1.0.0
Depends:	R (≥ 4.1.0)
Imports:	dplyr, ggalluvial, ggplot2, magrittr, pROC, purrr, readr, rlang, stats, tibble, tidyr, tidyselect, utils
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0), torch, xgboost (≥ 3.1.0)
Published:	2026-10-26
DOI:	10.32614/CRAN.package.fairGATE
Author:	Rhys Holland [aut, cre], Raquel Iniesta [aut]
Maintainer:	Rhys Holland <rhys.holland at icloud.com>
BugReports:	https://github.com/rhysholland/FairGATE/issues
License:	MIT + file LICENSE
URL:	https://github.com/rhysholland/FairGATE
NeedsCompilation:	no
SystemRequirements:	Optional 'LibTorch' backend for the neural-network components; install via torch::install_torch().
Language:	en-GB
Materials:	README, NEWS
CRAN checks:	fairGATE results

Documentation:

Reference manual:	fairGATE.html , fairGATE.pdf
Vignettes:	Introduction to fairGATE (source, R code)

Downloads:

Package source:	fairGATE_1.0.0.tar.gz
Windows binaries:	r-devel: fairGATE_0.1.1.zip, r-release: fairGATE_0.1.1.zip, r-oldrel: fairGATE_0.1.1.zip
macOS binaries:	r-release (arm64): fairGATE_1.0.0.tgz, r-oldrel (arm64): fairGATE_1.0.0.tgz, r-release (x86_64): fairGATE_1.0.0.tgz, r-oldrel (x86_64): fairGATE_1.0.0.tgz
Old sources:	fairGATE archive

Linking:

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