A Comparative Study of Divisive and Agglomerative Hierarchical Clustering Algorithms

Maurice Roux ()
Additional contact information
Maurice Roux: Faculté des Sciences de St-Jérôme

Journal of Classification, 2018, vol. 35, issue 2, No 7, 345-366

Abstract: Abstract A general scheme for divisive hierarchical clustering algorithms is proposed. It is made of three main steps: first a splitting procedure for the subdivision of clusters into two subclusters, second a local evaluation of the bipartitions resulting from the tentative splits and, third, a formula for determining the node levels of the resulting dendrogram. A set of 12 such algorithms is presented and compared to their agglomerative counterpart (when available). These algorithms are evaluated using the Goodman-Kruskal correlation coefficient. As a global criterion it is an internal goodness-of-fit measure based on the set order induced by the hierarchy compared to the order associated with the given dissimilarities. Applied to a hundred random data tables and to three real life examples, these comparisons are in favor of methods which are based on unusual ratio-type formulas to evaluate the intermediate bipartitions, namely the Silhouette formula, the Dunn's formula and the Mollineda et al. formula. These formulas take into account both the within cluster and the between cluster mean dissimilarities. Their use in divisive algorithms performs very well and slightly better than in their agglomerative counterpart.

Keywords: Hierarchical clustering; Dissimilarity data; Splitting procedures; Evaluation of hierarchy; Dendrogram; Ultrametrics (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://link.springer.com/10.1007/s00357-018-9259-9 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:35:y:2018:i:2:d:10.1007_s00357-018-9259-9

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

DOI: 10.1007/s00357-018-9259-9

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 ().