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.
Description
Import 29/09/2010
Subject(s)
K-means, Farthest first traversial, COBWEB/CLASSIT, clustering, DBscan, OPTICS, R-tree, KD-tree