COMPARATIVE ANALYSIS OF SELF-ORGANIZING MAP SYSTEMS Cover Image

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

Author(s): Pavel Stefanovič, Olga Kurasova
Subject(s): Education
Published by: Vilniaus Universiteto Leidykla

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.

  • Issue Year: 2009
  • Issue No: 50
  • Page Range: 334-339
  • Page Count: 6
  • Language: Lithuanian
Toggle Accessibility Mode