Outliers in rough k-means clustering

Authors:
Georg Peters
Affiliations:
Department of Computer Science, Munich University of Applied Sciences, Munich, Germany
Venue:
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Year:
2005

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Abstract

Recently rough cluster algorithm were introduced and successfully applied to real life data. In this paper we analyze the rough k-means introduced by Lingras’ et al. with respect to its compliance to the classical k-means, the numerical stability and its performance in the presence of outliers. We suggest a variation of the algorithm that shows improved results in these circumstances.