A Dimension-Independent Discriminant Between Distributions

Salimeh Yasaei Sekeh; Brandon Oselio; Alfred O. Hero III

ICASSP 2018accepted0 citations

A Dimension-Independent Discriminant Between Distributions

Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero III

Abstract

Henze-Penrose divergence is a non-parametric divergence measure that can be used to estimate a bound on the Bayes error in a binary classification problem. In this paper, we show that a cross-match statistic based on optimal weighted matching can be used to directly estimate Henze-Penrose divergence. Unlike an earlier approach based on the Friedman-Rafsky minimal spanning tree statistic, the proposed method is dimension-independent. The new approach is evaluated using simulation and applied to real datasets to obtain Bayes error estimates.

BibTeX

@inproceedings{icassp2018_adimensionindepe,
  title = {A Dimension-Independent Discriminant Between Distributions},
  author = {Salimeh Yasaei Sekeh and Brandon Oselio and Alfred O. Hero III},
  booktitle = {ICASSP 2018},
  year = {2018}
}