Authors: C. Tyler Diggans and A. R. AlMomani
Introduces Geometric Partition Entropy (GPE), a method for computing entropy of continuous random variables by leveraging the intrinsic geometry of the data through Delaunay tessellation. GPE eliminates the need for arbitrary binning or bandwidth choices, instead deriving partitions directly from the spatial structure of observations.
Explainable & Interpretable ML / AI (Pillar 2)