Self-organizing map (SOM) has been recognized as a powerful tool in cluster analysis. This paper presents a fuzzy SOM algorithm for mixed numeric and categorical data which integrates fuzzy set theory in model exploration through a fuzzy projection instead of crisp projection. In addition, a hybrid clustering approach is proposed combining SOMs with partitive clustering algorithms for the sake of visualization superiority and computational efficiency.
['Ning Chen', 'An Chen']
A Fuzzy and Hybrid Clustering Framework Using Self-Organizing Map