A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis

Autor/inn/en	Steinley, Douglas; Brusco, Michael J.
Titel	A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis
Quelle	In: Multivariate Behavioral Research, 43 (2008) 1, S.77-108 (32 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0027-3171
Schlagwörter	Test Items; Simulation; Multivariate Analysis; Data Analysis; Scores; Correlation; Comparative Analysis + Suchen Sie Ihr Suchwort? Test content; Testaufgabe; Simulation program; Simulationsprogramm; Multivariate Analyse; Auswertung; Korrelation
Abstract	A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these procedures are demonstrated in a simulation study, showing favorable results when compared with existing standardization methods. A detailed demonstration of the weighting and selection procedure is provided for the well-known Fisher Iris data and several synthetic data sets. (Contains 6 figures, 9 tables, and 3 footnotes.) (Author).
Anmerkungen	Lawrence Erlbaum. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals/default.html
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10