Clustering based on kolmogorov information

Authors:
Fouchal Said;Ahat Murat;Lavallée Ivan;Bui Marc;Benamor Sofiane
Affiliations:
Laboratoire d'Informatique et des Systèmes Complexes, Paris & CNRS UMI ESS, UCAD Dakar;Laboratoire d'Informatique et des Systèmes Complexes, Paris & CNRS UMI ESS, UCAD Dakar;Laboratoire d'Informatique et des Systèmes Complexes, Paris & CNRS UMI ESS, UCAD Dakar;Laboratoire d'Informatique et des Systèmes Complexes, Paris & CNRS UMI ESS, UCAD Dakar;Laboratoire d'Informatique et des Systèmes Complexes, Paris & CNRS UMI ESS, UCAD Dakar
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Year:
2010

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Abstract

In this paper we show how to reduce the computational cost of Clustering by Compression, proposed by Cilibrasi & Vitànyi, from O(n4) to O(n2). To that end, we adopte the Weighted Paired Group Method using Averages (WPGMA) method to the same similarity measure, based on compression, used in Clustering by Compression. Consequently, our proposed approach has easily classified thousands of data, where Cilibrasi & Vitànyi proposed algorithm shows its limits just for a hundred objects. We give also results of experiments.