We propose a tree-based algorithm (μCART) for classification and regression problems in the context of functional data analysis, which allows to leverage measure learning multiple splitting rules at node level, with objective reducing error while retaining interpretability tree. For each internal node, our main contribution is idea weighted space by means constrained convex optimization, then u...
