A python package that implements the black-box approach to fair classification described in the paper A Reductions Approach to Fair Classification.
Clone the repository locally git clone [email protected]:Microsoft/fairlearn.git. Verify that the package works by running python test_fairlearn.py in the root.
The function expgrad in the module fairlearn.classred implements the reduction of fair classification to weighted binary classification. Any learner that supports weighted binary classification can be provided as input for this reduction. Two common fairness definitions are provided in the module fairlearn.moments: demographic parity (class DP) and equalized odds (class EO). See the file test_fairlearn.py for example usage of expgrad.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repositories using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
fairlearn is maintained by:
- @MiroDudik
If you are the current maintainer of this project:
- Create a branch for the release:
git checkout -b release-vxx.xx - Ensure that all tests return "ok":
python test_fairlearn.py - Bump the module version in
fairlearn/__init__.py - Make a pull request to Microsoft/fairlearn
- Merge Microsoft/fairlearn pull request
- Tag and push:
git tag vxx.xx; git push --tags
Security issues and bugs should be reported privately, via email, to the Microsoft Security Response Center (MSRC) at [email protected]. You should receive a response within 24 hours. If for some reason you do not, please follow up via email to ensure we received your original message. Further information, including the MSRC PGP key, can be found in the Security TechCenter.