Totally Balanced Dissimilarities

François Brucker (), Pascal Préa () and Célia Châtel ()
Additional contact information
François Brucker: LIf, CNRS UMR 7279
Pascal Préa: LIf, CNRS UMR 7279
Célia Châtel: LIf, CNRS UMR 7279

Journal of Classification, 2020, vol. 37, issue 1, No 12, 203-222

Abstract: 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.

Keywords: Dissimilarities; Totally balanced hypergraphs; Binary matrices (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00357-019-09320-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jclass:v:37:y:2020:i:1:d:10.1007_s00357-019-09320-w

Ordering information: This journal article can be ordered from
http://www.springer. ... hods/journal/357/PS2

DOI: 10.1007/s00357-019-09320-w

Access Statistics for this article

Journal of Classification is currently edited by Douglas Steinley

More articles in Journal of Classification from Springer, The Classification Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().