Fairness constraint for binary classifiers asking that sensitive groups see comparable false-positive and true-positive rates.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains Equalized odds in context, with comparison tables and the common traps.
Related terms
- ExponentiatedGradient
A Fairlearn reduction method: it wraps a binary classification estimator and repeatedly retrains it on reweighted data so the result meets equalized odds or demographic parity.
- ThresholdOptimizer
A post-processing algorithm in Fairlearn that sets separate thresholds per group on an already-trained binary classifier, targeting equalized odds or demographic parity with no retraining.