uiuctml/fair-classification
Post-processing for fair classification
This project helps ensure fairness in automated decision-making systems that predict outcomes like loan approvals or hiring recommendations. It takes existing prediction models and adjusts their outputs to prevent biased results based on sensitive attributes. Data scientists, machine learning engineers, and ethicists can use this to create more equitable AI systems.
No commits in the last 6 months.
Use this if you have a classification model and need to adjust its predictions to meet specific fairness criteria like statistical parity or equal opportunity.
Not ideal if you are looking for a tool to build a classification model from scratch, as this focuses only on post-processing existing model outputs.
Stars
16
Forks
2
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 30, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/uiuctml/fair-classification"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
fairlearn/fairlearn
A Python package to assess and improve fairness of machine learning models.
Trusted-AI/AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations...
holistic-ai/holisticai
This is an open-source tool to assess and improve the trustworthiness of AI systems.
microsoft/responsible-ai-toolbox
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment...
datamllab/awesome-fairness-in-ai
A curated list of awesome Fairness in AI resources