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Journal of Classification
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30-03-2019

Totally Balanced Dissimilarities

Authors: François Brucker, Pascal Préa, Célia Châtel

Published in: Journal of Classification | Issue 1/2020

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Abstract

We show in this paper a bijection between totally balanced hypergraphs and so-called totally balanced dissimilarities. We give an efficient way (O(n3) where n is the number of elements) to (i) recognize if a given dissimilarity is totally balanced and (ii) approximate it if it is not the case. We also introduce a new kind of dissimilarity which generalizes chordal graphs and allows a polynomial number of clusters that can be easily computed and interpreted.
previous article Clustering Analysis of a Dissimilarity: a Review of Algebraic and Geometric Representation
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Metadata
Title
Totally Balanced Dissimilarities
Authors
François Brucker
Pascal Préa
Célia Châtel
Publication date
30-03-2019
Publisher
Springer US
Published in
Journal of Classification / Issue 1/2020
Print ISSN: 0176-4268
Electronic ISSN: 1432-1343
DOI
https://doi.org/10.1007/s00357-019-09320-w

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