Trimmed fuzzy clustering for interval-valued data

Pierpaolo D’Urso (), Livia Giovanni and Riccardo Massari
Authors registered in the RePEc Author Service: Pierpaolo D'Urso

Advances in Data Analysis and Classification, 2015, vol. 9, issue 1, 40 pages

Abstract: In this paper, following a partitioning around medoids approach, a fuzzy clustering model for interval-valued data, i.e., FCMd-ID, is introduced. Successively, for avoiding the disruptive effects of possible outlier interval-valued data in the clustering process, a robust fuzzy clustering model with a trimming rule, called Trimmed Fuzzy $$C$$ C -medoids for interval-valued data (TrFCMd-ID), is proposed. In order to show the good performances of the robust clustering model, a simulation study and two applications are provided. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Interval-valued data; Partitioning around medoids; Fuzzy clustering; Robust clustering; Trimming; Web advertising; 62H30; 62G35; 03E72; 62A86 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11634-014-0169-3

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