Also known as: Post processing
Adjusting the output of a model after the model has been run. Post-processing can be used to enforce fairness constraints without modifying models themselves. For example, one might apply post-processing to a binary classification model by setting a classification threshold such that equality of opportunity is maintained for some attribute by checking that the true positive rate is the same for all values of that attribute.