Incorporating Fuzziness to CLARANS

  • Sampreeti Ghosh
  • Sushmita Mitra
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5909)

Abstract

In this paper we propose a way of handling fuzziness while mining large data. Clustering Large Applications based on RANdomized Search (CLARANS) is enhanced to incorporate the fuzzy component. A new scalable approximation to the maximum number of neighbours, explored at a node, is developed. The goodness of the generated clusters is evaluated in terms of validity indices. Experimental results on various data sets is run to converge to the optimal number of partitions.

Keywords

Data mining CLARANS medoid fuzzy sets clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sampreeti Ghosh
    • 1
  • Sushmita Mitra
    • 1
  1. 1.Center for Soft ComputingIndian Statistical InstituteKolkataIndia

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