Divisive monothetic clustering for interval and histogram-valued data

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

brito, p (Author) FEP; chavent, m (Author) Other

Conference proceedings International

Title: ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods

Pages: 229-234

1st International Conference on Pattern Recognition Applications and Methods, ICPRAM 2012

Vilamoura, Algarve, 6 February 2012 through 8 February 2012

Indexing

ISI Web of Knowledge

Scopus - 7 Citations

Scientific classification

CORDIS: Physical sciences > Mathematics > Statistics

Other information

Authenticus ID: P-008-4CM

Abstract (EN): In this paper we propose a divisive top-down clustering method designed for interval and histogram-valued data. The method provides a hierarchy on a set of objects together with a monothetic characterization of each formed cluster. At each step, a cluster is split so as to minimize intra-cluster dispersion, which is measured using a distance suitable for the considered variable types. The criterion is minimized across the bipartitions induced by a set of binary questions. Since interval-valued variables may be considered a special case of histogram-valued variables, the method applies to data described by either kind of variables, or by variables of both types. An example illustrates the proposed approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6