Equality of Odds

nounverified·updated Aug 28, 2026

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The probability of a person in the positive class being correctly assigned a positive outcome and the probability of a person in a negative class being incorrectly assigned a positive outcome should both be the same for the protected and unprotected group members. In other words, the protected and unprotected groups should have equal rates for true positives and false positives.

MWEA Survey on Bias and Fairness in Machine Learning

Senses

1 more sense beyond the canonical

Equality of Opportunity in Supervised Learning

(Equalized odds). We say that a predictor bY satisfies equalized odds with respect to protected attribute A and outcome Y, if bY and A are independent conditional on Y.

Classifications

per-axis with provenance

Entity Type

Requirement75%llm-generatedllm:claude-haiku-4-5

?unassignedlast reviewed —

Sensitivity

unclassified

Information Class

unclassified

Variants

2 surface forms

possessive: Equality of Odds's
pluralpossessive: Equality of Oddses'

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