Bias mitigation algorithms in ML are highly sensitive to hyperparameters, and most can achieve comparable fairness-accuracy tradeoffs once hyperparameter optimization is allowed, so single-setting benchmarks can mislead.
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Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML
Bias mitigation algorithms in ML are highly sensitive to hyperparameters, and most can achieve comparable fairness-accuracy tradeoffs once hyperparameter optimization is allowed, so single-setting benchmarks can mislead.