Abstract
The aim of the present paper is to discuss methods for selecting a subset of initially observed variables in the context of fuzzy clustering. The suggested procedure is based on the optimization of an objective function which is differently specified according to the purpose of the selection. Measure of cluster validity, a generalization of Rand index and distance between dissimilarity matrices are then proposed as proper functions to optimize.
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References
Bandemer, H. and Näther, W. (1992), Fuzzy Data Analysis, Kluwer, Dordrecht.
Bezdek, J. C. (1981), Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York.
Fowlkes, E. B., Gnanadesikan, R. and Kettenring, J. R. (1988), Variable selection in clustering, Journal of Classification, 5, 205–228.
Kaufmann, L. and Rousseeuw, P.G. (1990), Finding Groups in Data, Wiley, New York.
Leung, Y. (1988), Spatial Analysis and Planning under Imprecision, North Holland, Amsterdam.
Libert, G. and Roubens, M. (1983), New Experimental Results in Cluster Validity of Fuzzy Clustering Algorithms, New Trend in Data Analysis and Application, Janssen J., Marcotorchino J. F. and Proth J. M. (eds.), North Holland, 205–218.
Milioli, M. A. (1993), Variabili ridondanti e osservazioni influenti nell’analisi dei dati multidimensionali, Collana di Studi e Ricerche della Facoltà di Economia e Commercio, Università degli Studi di Parma, Giuffrè, Milano.
Milioli, M. A. (1994), Confronto fra partizioni sfocate nell’analisi di dati territoriali, Atti della XXXVII Riunione Scientifica della Società Italiana di Statistica, 43–50.
Zani, S. (1988), Un metodo di classificazione sfocata, in: G. Diana, C. Provasi and R. Vedaldi (a cura di) Metodi statistici per la tecnologia e l’analisi dei dati multidimensionali, Università degli Studi di Padova, 281–288.
Zimmermann, H. J. (1985), Fuzzy Set Theory and Its Applications, Kluwer, Dordrecht.
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© 1999 Springer-Verlag Berlin · Heidelberg
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Milioli, M.A. (1999). Variable Selection In Fuzzy Clustering. In: Vichi, M., Opitz, O. (eds) Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60126-2_9
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DOI: https://doi.org/10.1007/978-3-642-60126-2_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65633-3
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