A weighted linear interaction model with per-group lasso penalties improves small-subgroup prediction accuracy while staying interpretable.
Automating procedurally fair feature selection in machine learning
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Maximizing Predictive Performance for Small Subgroups: Functionally Adaptive Interaction Regularization (FAIR)
A weighted linear interaction model with per-group lasso penalties improves small-subgroup prediction accuracy while staying interpretable.