#8 ENH Add mitigation algorithm from - #21
Open
Aryan1296 wants to merge 3 commits into
Open
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
#8 ENH Add mitigation algorithm from
This pull request implements the pre-processing mitigation algorithm described in the paper "Optimized Pre-Processing for Discrimination Prevention" by Calmon et al. This algorithm is a powerful addition to Fairlearn's mitigation toolkit, as it works to achieve group fairness (demographic parity) while simultaneously constraining the amount of distortion introduced to individual data points.
The implementation is based on the original work by the authors and is similar to the OptimPreproc algorithm found in AI Fairness 360.
This PR addresses all the requirements outlined in the corresponding issue, including the core algorithm, unit tests, API documentation, and a user guide entry.
Checklist of Changes:
Algorithm Implementation: The OptimizedPreproc class has been added to fairlearn.preprocessing.
Unit Tests: A comprehensive suite of unit tests has been created in test.unit.preprocessing to validate the algorithm's functionality and correctness.
API Documentation: The class docstring includes a detailed API reference explaining the parameters, attributes, and methods, making it easy for users to integrate.
User Guide: A new section has been added to docs.user_guide.mitigation.rst to briefly explain the technique and guide users on its application.