A comparative analysis of selected methods of cluster analysis in the grouping units with a complex group structure
Journal Title: Zarządzanie i Finanse - Year 2013, Vol 11, Issue 3
Abstract
The aim of this article is a comparative analysis of selected classical clustering methods, with hybrid methods based on self-learning neural network type Self Organizing (SOM) and Growing Neural Gas (GNG). It has been shown experimentally that in distinguishing complex spatial structures of the units, most commonly used classical methods may be ineffective. The better results were obtained from the included methods for a hybrid neural network SOM+GNG. It was also shown that the test cases used alone GNG network is characterized highlighting the best of the properties of clusters of all of these methods.
Authors and Affiliations
Kamila Migdał-Najman, Krzysztof Najman
Keywords
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