Fair Class Balancing

This repository contains a sample implementation of Fair Class Balancing. For more information, see our paper Fair Class Balancing: Enhancing Model Fairness without Observing Sensitive Attributes published on CIKM 2020.

Dependencies

• sklearn
• imblearn
• matplotlib
• tabulate

Cite This Work

Below is the bibtex entry for this paper.

@inproceedings{10.1145/3340531.3411980,
author = {Yan, Shen and Kao, Hsien-te and Ferrara, Emilio},
title = {Fair Class Balancing: Enhancing Model Fairness without Observing Sensitive Attributes},
year = {2020},
isbn = {9781450368599},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3340531.3411980},
doi = {10.1145/3340531.3411980},
booktitle = {Proceedings of the 29th ACM International Conference on Information & Knowledge Management},
pages = {1715–1724},
numpages = {10},
keywords = {class balancing, bias, fairness},
location = {Virtual Event, Ireland},
series = {CIKM '20}
}