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Trimmed fuzzy clustering for interval-valued data

  • Pierpaolo D’UrsoEmail author
  • Livia De Giovanni
  • Riccardo Massari
Regular Article

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 \(C\)-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.

Keywords

Interval-valued data Partitioning around medoids Fuzzy clustering Robust clustering Trimming Web advertising 

Mathematics Subject Classification

62H30 62G35 03E72 62A86 

Notes

Acknowledgments

The authors thank the editors and the three referees for their useful comments and suggestions which helped to improve the quality and presentation of this manuscript.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Pierpaolo D’Urso
    • 1
    Email author
  • Livia De Giovanni
    • 2
  • Riccardo Massari
    • 1
  1. 1.Dipartimento di Scienze Sociali ed EconomicheSapienza, Università di RomaRomeItaly
  2. 2.Dipartimento di Scienze PoliticheLUISS Guido CarliRomeItaly

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