Smooth And Consistent Probabilistic Regression Trees

no code implementations • NeurIPS 2020 • Sami Alkhoury, Emilie Devijver, Marianne Clausel, Myriam Tami, Eric Gaussier, Georges Oppenheim

We propose here a generalization of regression trees, referred to as Probabilistic Regression (PR) trees, that adapt to the smoothness of the prediction function relating input and output variables while preserving the interpretability of the prediction and being robust to noise.

regression