An extension of self-organizing maps to categorical data

Authors:
Ning Chen;Nuno C. Marques
Affiliations:
Institute of Mechanics, Chinese Academy of Sciences, P.R. China;CENTRIA/Departamento de Informtica, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
Venue:
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Year:
2005

Citing 8
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Abstract

Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on categorical data is still a challenge for SOM. This paper aims to extend standard SOM to handle feature values of categorical type. A batch SOM algorithm (NCSOM) is presented concerning the dissimilarity measure and update method of map evolution for both numeric and categorical features simultaneously.