Variable Selection In Fuzzy Clustering

Milioli, Maria Adele

doi:10.1007/978-3-642-60126-2_9

Variable Selection In Fuzzy Clustering

Maria Adele Milioli⁶

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Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization ((STUDIES CLASS))

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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Authors and Affiliations

Istituto di Statistica, Facoltà di Economia, Univ. of Parma, Italy
Maria Adele Milioli

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Maria Adele Milioli
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Editors and Affiliations

Dipartimento Metodi Quantitativi e Teoria Economica, University “G. D’Annunzio” di Chieti, Viale Pindaro 42, I-65127, Pescara, Italy
Maurizio Vichi
Lehrstuhl für Mathematische Methoden der Wirtschaftswissenschaften, University of Augsburg, D-86135, Augsburg, Germany
Otto Opitz

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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
Online ISBN: 978-3-642-60126-2
eBook Packages: Springer Book Archive

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