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Counterfactual Averaging For Fair Predictions Cafp

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paper · 2026-04-09
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In this paper, we propose Counterfactual Averaging for Fair Predictions (CAFP), a model-agnostic post-processing method that mitigates unfair influence from protected attributes without retraining or modifying the original classifier.

Counterfactual Model Averaging for Fair ML Predictions