Incorporating Fuzziness to CLARANS

Authors:
Sampreeti Ghosh;Sushmita Mitra
Affiliations:
Center for Soft Computing, Indian Statistical Institute, Kolkata, India 700108;Center for Soft Computing, Indian Statistical Institute, Kolkata, India 700108
Venue:
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Year:
2009

Citing 7
Cited 0

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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.