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Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Scatter Search Algorithm for the Automatic Clustering Problem
verfasst von : Rasha S. Abdule-Wahab, Nicolas Monmarché, Mohamed Slimane, Moaid A. Fahdil, Hilal H. Saleh
Erschienen in: Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Verlag: Springer Berlin Heidelberg
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We present a new hybrid algorithm for data clustering. This new proposal uses one of the well known evolutionary algorithms called Scatter Search. Scatter Search operates on a small set of solutions and makes only a limited use of randomization for diversification when searching for globally optimal solutions. The proposed method discovers automatically cluster number and cluster centres without prior knowledge of a possible number of class, and without any initial partition. We have applied this algorithm on standard and real world databases and we have obtained good results compared to the K-means algorithm and an artificial ant based algorithm, the Antclass algorithm.