Application of Monotonic Constraints in Machine Learning Models

After significant progress in data science and artificial intelligence, we have started hearing discussions around ethical and explainable AI, especially in highly regulated industries like banking and insurance. Though plenty of easily accessible and highly predictive algorithms are available, analysts and data scientists working in these industries face a dilemma between choosing predictive accuracy or honoring their regulatory responsibilities. Researchers and industry experts are trying hard to make machine learning models transparent and interpretable.

One such innovation that makes the model output more practical is called monotonic constraints.