https://github.com/algofairness/fairness-comparison

Comparing fairness-aware machine learning techniques.
https://github.com/algofairness/fairness-comparison

Last synced: 2 months ago
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Comparing fairness-aware machine learning techniques.

• Host: GitHub
• URL: https://github.com/algofairness/fairness-comparison
• Owner: algofairness
• License: other
• Created: 2017-02-05T20:01:05.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2022-12-26T20:27:03.000Z (over 1 year ago)
• Last Synced: 2024-01-07T01:43:57.460Z (5 months ago)
• Language: HTML
• Homepage:
• Size: 331 MB
• Stars: 154
• Watchers: 17
• Forks: 49
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Changelog: changelog.md
  • License: LICENSE.txt

Lists

• awesome-production-machine-learning - Fairness Comparison - comparison.svg?style=social) - This repository is meant to facilitate the benchmarking of fairness aware machine learning algorithms based on [this paper](https://arxiv.org/abs/1802.04422). (Explaining Black Box Models and Datasets)
• awesome-machine-learning-interpretability - fairness-comparison - comparison?style=social) | "meant to facilitate the benchmarking of fairness aware machine learning algorithms.” | (Technical Resources / Open Source/Access Responsible AI Software Packages)
• awesome-fairness-in-ai - fairness: Benchmarking of fairness aware machine learning algorithms
• awesome-production-machine-learning - fairness - comparison.svg?style=social) - This repository is meant to facilitate the benchmarking of fairness aware machine learning algorithms based on [this paper](https://arxiv.org/abs/1802.04422). (Explaining Black Box Models and Datasets)
• Awesome-AIML-Data-Ops - fairness - comparison.svg?style=social) - This repository is meant to facilitate the benchmarking of fairness aware machine learning algorithms based on [this paper](https://arxiv.org/abs/1802.04422). (Explaining Black Box Models and Datasets)
• awesome-production-machine-learning - fairness - comparison.svg?style=social) - This repository is meant to facilitate the benchmarking of fairness aware machine learning algorithms based on [this paper](https://arxiv.org/abs/1802.04422). (Explaining Black Box Models and Datasets)
• awesome-algofairness - Fairness comparison
• awesome-ai-fairness - Fairness Comparison