Shlukování pomocí algoritmu COBWEB

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Authors

Vicher, Martin

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Vysoká škola báňská - Technická univerzita Ostrava

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Abstract

This diploma thesis is about clustering algorithms, their clasification and implementation of several choosen clustering algorithms. These choosen clustering algorithms were optimalized for processing high number of high dimensional objects. In this paper was found, that not all from these choosen clustering algorithms are suitable for processing high number of high dimensional objects. At the conclusion, properties of these chosen algorithms were experimentally verified.

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Import 29/09/2010

Subject(s)

K-means, Farthest first traversial, COBWEB/CLASSIT, clustering, DBscan, OPTICS, R-tree, KD-tree

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