In-processing

Classically, to estimate a model, we look for a model (in a pre-defined class) that minimizes a prediction error, or that maximizes the accuracy. If the model is required to satisfy constraints, a natural idea is to add a penalty term in the objective function. The idea of “in-processing” is to get a trade-off between accuracy and fairness. As previously, we present that approach to some datasets.