Subgroup Fairness, Instantaneous Fairness, and Distributional Repair #550
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- Distributional Repair - Subgroup Fairness - Instantaneous Fairness Algorithms and their respective tests and examples are added.
Masters Project Submission
- Distributional Repair - Instantaneous Repair - Subgroup Repair
…oeJohnson01/AIF360 into PracticalAspectsOfFairnessInAI
Added new algorithms to Read Me document
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Subgroup Fairness, Instantaneous Fairness, and Distributional Repair
The Subgroup Fairness and Instantaneous Fairness algorithms focus on minimizing disparities between different groups over time and across subgroups. These algorithms expand on a conventional fairness model to address scenarios where fairness might vary over different time periods or among subgroups with multiple sensitive attributes.
The Distributional Repair algorithm focuses on conditional independence. The idea is to reduce the correlation between sensitive and non-sensitive features in a dataset through use of an OT plan, increasing fairness in the dataset ahead of training.
Related Paper
For additional information, and results of model evaluation, please refer to the paper linked below, written by myself as part of my Masters Dissertation at Imperial College London
Practical_Aspects_of_Fairness_in_AI (1).pdf
References:
Abigail Langbridge, Anthony Quinn, and Robert Shorten
Quan Zhou, Jakub Marecek, and Robert N. Shorten
Closes #549