Minimum Sum of Squares Clustering in a Low Dimensional Space

P Hansen, B Jaumard and N Mladenovic

Working Papers from Ecole des Hautes Etudes Commerciales de Montreal-

Abstract: Clustering with a criterion which minimizes the sum of squared distances to cluster centroids is usually done in a heuristic way. An exact polunomial algorithm is proposed for minimum sum of squares hierarchical divisive clustering of points in a p-dimensional space with small p.

Keywords: STATISTICS (search for similar items in EconPapers)
JEL-codes: C35 (search for similar items in EconPapers)
Pages: 21 pages
Date: 1996
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:fth:etcomo:96-18

Access Statistics for this paper

More papers in Working Papers from Ecole des Hautes Etudes Commerciales de Montreal- Canada; ECOLE DES HAUTES ETUDES COMMERCIALES (H.E.C.), 5255 DECELLES MONTREAL H3T 1V6 QUEBEC. Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Krichel ().