Equalized Opportunity Testing

From The Foundation for Best Practices in Machine Learning

Equalized Opportunity Testing


If applicable, test Model(s) for equalized opportunity. Evaluate whether Model(s) predict a Positive Outcome for (Sub)population members that are actually in the positive class at the same rates as across (Sub)populations.


To (a) ensure that (Sub)population members who should receive the Positive Outcome are receiving the Positive Outcome as often as their peers; and (b) highlight associated risks that might occur in the Product Lifecycle.

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