Neural unit shape representation: A new SOM-based visualisation

Article type: Research Article

Authors: Tan, Hiong Sen^{; *} | George, Susan E.

Affiliations: University of South Australia

Correspondence: [*] Corresponding author. E-mail: [email protected]

Abstract: The Self Organising Map (SOM) is an artificial neural network technique that has been successfully applied in clustering and visualisation tasks in data mining. In this paper, we propose a new SOM-based visualisation, Neural Unit Shape Representation. Its advantage over the previous SOM-based visualisation, U-matrix and Component Planes, is that it gives visual cues to the properties of individual neural units or nodes on the map, enabling direct examination of the produced ordering. Further, the combination of the Neural Unit Shape Representation and a new way of drawing boundaries using U-matrix gives a good visualisation and helps people, even without prior knowledge of data, to find interesting patterns.

Keywords: Self organising map, clustering, visualisation, data mining

DOI: 10.3233/KES-2005-9306

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 9, no. 3, pp. 223-230, 2005