SAVIORGANIZUOJANČIŲ NEURONINIŲ TINKLŲ SISTEMŲ LYGINAMOJI ANALIZĖ
COMPARATIVE ANALYSIS OF SELF-ORGANIZING MAP SYSTEMS

Summary/Abstract: In the article, we compare three systems of self-organizing maps: NeNet, SOM-Toolbox and Databionic ESOM. The main target of the usage of the systems is data clustering and their graphical presentation on the self-organizing map (SOM). The self-organizing maps are one of types of artifi cial neural networks. The SOM systems are different one from other in their interfaces, the data pre-processing, learning rules, visualization manners, etc. Similarities and differences of the systems have been highlighted here. The experiments have been carried out with two data sets: iris and glass. Quantization and topographic errors of SOMs have been estimated, too.

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