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arXiv · 1802.04497

A Dimension-Independent discriminant between distributions

Salimeh Yasaei Sekeh·Brandon Oselio·Alfred O. Hero
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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.

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Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero. 2018-02-13. A Dimension-Independent discriminant between distributions. https://arxiv.org/abs/1802.04497

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