Quantitative Analysis of Similarity Measures of Distributions

Abstract : The Earth Mover's Distance (EMD) is a metric based on the theory of optimal transport that has interesting geometrical properties for distributions comparison. However, the use of this measure is limited in comparison with other similarity measures as the Kullback-Leibler divergence. The main reason was, until recently, the computation complexity. In this paper, we present a comparative study of the dissimilarity measures most used in the literature for the comparison of distributions through a color-based image classification system and other simple examples with synthetic data. We show that today the EMD is a computa-tionally efficient measure that better reflects the similarity between two distributions.
Type de document :
Pré-publication, Document de travail
2019
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https://hal.archives-ouvertes.fr/hal-01984970
Contributeur : Eric Bazan <>
Soumis le : jeudi 17 janvier 2019 - 14:48:05
Dernière modification le : dimanche 20 janvier 2019 - 01:09:51

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ismm19.pdf
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  • HAL Id : hal-01984970, version 1

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Eric Bazan, Petr Dokládal, Eva Dokladalova. Quantitative Analysis of Similarity Measures of Distributions. 2019. 〈hal-01984970〉

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