fairGATE
Fair Gated Algorithm for Targeted Equity
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling source/ R- | fairGATE_0.1.1.tar.gz |
313.5 KiB |
0.1.1 |
latest source/ R- | fairGATE_0.1.1.tar.gz |
313.5 KiB |
0.1.1 |
2026-04-23 source/ R- | fairGATE_0.1.1.tar.gz |
313.5 KiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | fairGATE_0.1.1.zip |
392.7 KiB |