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IDA
2003
Springer

An Iterated Local Search Approach for Minimum Sum-of-Squares Clustering

14 years 3 months ago
An Iterated Local Search Approach for Minimum Sum-of-Squares Clustering
Abstract. Since minimum sum-of-squares clustering (MSSC) is an NPhard combinatorial optimization problem, applying techniques from global optimization appears to be promising for reliably clustering numerical data. In this paper, concepts of combinatorial heuristic optimization are considered for approaching the MSSC: An iterated local search (ILS) approach is proposed which is capable of finding (near-)optimum solutions very quickly. On gene expression data resulting from biological microarray experiments, it is shown that ILS outperforms multi–start k-means as well as three other clustering heuristics combined with k-means.
Peter Merz
Added 07 Jul 2010
Updated 07 Jul 2010
Type Conference
Year 2003
Where IDA
Authors Peter Merz
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