Multi-class Bayes error estimation with a global minimal spanning tree

Henze-Penrose (HP) divergence has been used in many information theory, statistics and machine learning contexts, including the estimation of two-class Bayes classification error. Previous work has shown HP divergence can be directly estimated using the Friedman-Rafsky (FR) multivariate run test statistic. For the multi-class classification problem, HP divergence can also be used to bound the Bayes error by estimating the sum of pairwise Bayes...