Package: fairGNN
Title: Fairness-Aware Gated Neural Networks
Version: 0.1.0
Authors@R: 
    person("Rhys", "Holland", , "rhys.holland@icloud.com", role = c("aut", "cre"))
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
Suggests: knitr, torch, testthat, readxl, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/rhysholland/fairGNN
BugReports: https://github.com/rhysholland/fairGNN/issues
Depends: R (>= 4.1.0)
SystemRequirements: Optional 'LibTorch' backend; install via
        torch::install_torch().
NeedsCompilation: no
Packaged: 2026-10-06 10:13:30 UTC; root
Author: Rhys Holland [aut, cre]
Maintainer: Rhys Holland <rhys.holland@icloud.com>
Config/pak/sysreqs: libicu-dev libx11-dev
Repository: https://rhysholland.r-universe.dev
Date/Publication: 2025-10-26 20:33:49 UTC
RemoteUrl: https://github.com/cran/fairGNN
RemoteRef: HEAD
RemoteSha: c9ca1a118f20fea0af045321209166deed61d6f1