A Fuzzy and Hybrid Clustering Framework Using Self-Organizing Map

Ning Chen; An Chen

doi:10.1109/fskd.2008.149

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JOURNAL ARTICLE

A Fuzzy and Hybrid Clustering Framework Using Self-Organizing Map

Ning Chen An Chen

Year: 2008 Vol: 3808 Pages: 82-86

DOI: 10.1109/fskd.2008.149

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Abstract

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.

Keywords:

Computer science Cluster analysis Categorical variable Fuzzy logic Self-organizing map Fuzzy clustering Data mining Projection (relational algebra) Artificial intelligence Fuzzy set Visualization Pattern recognition (psychology) Machine learning Algorithm

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Advanced Clustering Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

A Fuzzy and Hybrid Clustering Framework Using Self-Organizing Map

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