A coevolutionary approach for clustering with feature weighting application to image analysis

Authors:
Alexandre Blansché;Pierre Gançarski;Jerzy J. Korczak
Affiliations:
LSIIT, UMR 7005 CNRS-ULP, Illkirch, France;LSIIT, UMR 7005 CNRS-ULP, Illkirch, France;LSIIT, UMR 7005 CNRS-ULP, Illkirch, France
Venue:
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Year:
2005

Citing 11
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Abstract

This paper presents a new process for modular clustering of complex data, such as that used in remote sensing images. This method performs feature weighting in a wrapper approach. The proposed method combines several local specialists, each one extracting one cluster only and using different feature weights. A new clustering quality criterion, adapted to independant clusters, is defined. The weight learning is performed through a cooperative coevolution algorithm, where each species represents one of the clusters to be extracted.