Abstract
We highlight a partition clustering method, which proposes an experimental solution to the famous problem of automatic discovery of the number of clusters (k). The majority of partition clustering methods consider the manual valuation of k. Manual valuation of k may be interesting for specific domains of applications where the expert has an accurate idea of the number of clusters he wants, however it is unrealistic for generic applications, and needs important estimation efforts without any insurance of their efficiencies.
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Fernandez, G., Meckaouche, A., Peter, P., Djeraba, C. (2002). Intelligent Image Clustering. In: Chaudhri, A.B., Unland, R., Djeraba, C., Lindner, W. (eds) XML-Based Data Management and Multimedia Engineering — EDBT 2002 Workshops. EDBT 2002. Lecture Notes in Computer Science, vol 2490. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36128-6_24
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DOI: https://doi.org/10.1007/3-540-36128-6_24
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