Approximate bicluster and tricluster boxes in the analysis of binary data

Authors:
Boris G. Mirkin;Andrey V. Kramarenko
Affiliations:
National Research University, Higher School of Economics, Moscow, Russia and Department of Computer Science and Information Systems, Birkbeck University of London, UK;National Research University, Higher School of Economics, Moscow, Russia
Venue:
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Year:
2011

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Abstract

A disjunctive model of box bicluster and tricluster analysis is considered. A least-squares locally-optimal one cluster method is proposed, oriented towards the analysis of binary data. The method involves a parameter, the scale shift, and is proven to lead to "contrast" box biand tri-clusters. An experimental study of the method is reported.