Subgroup Fairness, Instantaneous Fairness, and Distributional Repair - v2 #551
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- Distributional Repair - Subgroup Fairness - Instantaneous Fairness Algorithms and their respective tests and examples are added. Signed-off-by: Abi-Langbridge1 <Abi.Langbridge1@ibm.com>
* rename bias_scan->MDSS_bias_scan (kept bias_scan as well for backwards compat) Signed-off-by: Abi-Langbridge1 <Abi.Langbridge1@ibm.com>
Signed-off-by: Abi-Langbridge1 <Abi.Langbridge1@ibm.com>
- Distributional Repair - Instantaneous Repair - Subgroup Repair Signed-off-by: Abi-Langbridge1 <Abi.Langbridge1@ibm.com>
* bugfix: drop_above arg used hard-coded names, removed * FACTS hotfix: drop_infeasible set to False this part of the code is problematic due to the use of hardcoded feature names. The required functionality should be achieved in some other way. * FACTS bugfix: feat weights were not passed properly * removed obsolete use of drop_above argument * FACTS: added test for user interface API * FACTS_bias_scan: test improvement Previously, the test case only had inf costs. Consequently, the exact values of the feature weights were not actually tested properly. Signed-off-by: Abi-Langbridge1 <Abi.Langbridge1@ibm.com>
Signed-off-by: Abi-Langbridge1 <Abi.Langbridge1@ibm.com>
Signed-off-by: Abi-Langbridge1 <Abi.Langbridge1@ibm.com>
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@rahulnair23 moving discussion here as I had to fork Joe's repo |
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Apologies for the delay @Langbridge . I've missed reviewing this earlier. Could you check dependencies again? I'm getting a missing module error ( Thanks for including the downstream task. This is useful. Could you also report a fairness measure for this (the last cell of the demonstrator). It would help motivate users to use your methods as bias mitigation. Let me know if you need guidance on other items from my previous review:
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Updates to @JoeJohnson01's PR #550 (see original PR for references) to close #549