Package: fairGATE
Title: Fair Gated Algorithm for Targeted Equity
Version: 0.1.1
Authors@R: 
    c(
      person("Rhys", "Holland", email = "rhys.holland@icloud.com",
             role = c("aut", "cre")),
      person("Raquel", "Iniesta", 
             email = "raquel.iniesta@kcl.ac.uk",
             role = "aut")
    )
Description: Tools for training and analysing fairness-aware gated neural 
    networks for subgroup-aware prediction and interpretation in clinical datasets. 
    Methods draw on prior work in mixture-of-experts neural networks by
    Jordan and Jacobs (1994) <doi:10.1007/978-1-4471-2097-1_113>,
    fairness-aware learning by Hardt, Price, and Srebro (2016) <doi:10.48550/arXiv.1610.02413>,
    and personalised treatment prediction for depression by Iniesta, Stahl, and McGuffin (2016) 
    <doi:10.1016/j.jpsychires.2016.03.016>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: dplyr, tibble, ggplot2, readr, pROC, magrittr, tidyr, purrr,
        utils, stats, ggalluvial, tidyselect, rlang
Suggests: knitr, torch, testthat, readxl, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/rhysholland/FairGATE
BugReports: https://github.com/rhysholland/FairGate/issues
Depends: R (>= 4.1.0)
SystemRequirements: Optional 'LibTorch' backend; install via
        torch::install_torch().
LazyData: true
NeedsCompilation: no
Packaged: 2025-12-08 12:27:22 UTC; rhysholland
Author: Rhys Holland [aut, cre],
  Raquel Iniesta [aut]
Maintainer: Rhys Holland <rhys.holland@icloud.com>
Repository: CRAN
Date/Publication: 2025-12-08 13:00:12 UTC
Built: R 4.6.0; ; 2026-04-26 18:09:27 UTC; unix
