This code is the official implementation of Fair Classification with Group-Dependent Label Noise.
To install requirements:
pip install -r requirements.txt
To run the code
python3 run.py
Specifically, the surrogate loss function and the group peer loss function is implemented in PeerLoss.py.
The proxy fairness constraints are implemented in ProxyConstraint.py. The code for data preprocessing is
in datasets.py. utils.py defines some utility functions.
If you found this code useful for your research, please cite the following paper:
Jialu Wang, Yang Liu, and Caleb Levy. 2021. Fair Classification with Group-Dependent Label Noise. In ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21), March 1–10, 2021, Virtual Event, Canada. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3442188.3445915