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