A robust fuzzy k-means clustering model for interval valued data

Authors:
Pierpaolo D'Urso;Paolo Giordani
Affiliations:
Dipartimento di Scienze Economiche, Gestionali e Sociali, Università degli Studi del Molise, Campobasso, Italy 86100;Dipartimento di Statistica Probabilità e Statistiche Applicate, Università di Roma "La Sapienza", Rome, Italy 00185
Venue:
Computational Statistics
Year:
2006

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Abstract

In this paper a robust fuzzy k-means clustering model for interval valued data is introduced. The peculiarity of the proposed model is the capability to manage anomalous interval valued data by reducing the effects of such outliers in the clustering model. In the interval case, the concept of anomalous data involves both the center and the width (the radius) of an interval. In order to show how our model works the results of a simulation experiment and an application to real interval valued data are discussed.