A Fuzzy and Hybrid Clustering Framework Using Self-Organizing Map

Author

Chen, Ning ; Chen, An

Author_Institution

Inst. of Eng., Polytech. Inst. of Porto, Porto

Volume

1

fYear

2008

fDate

18-20 Oct. 2008

Firstpage

82

Lastpage

86

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

fuzzy set theory; pattern clustering; self-organising feature maps; statistical analysis; cluster analysis; fuzzy clustering framework; fuzzy projection; hybrid clustering framework; integrates fuzzy set theory; partitive clustering algorithms; self-organizing map; Clustering algorithms; Computational efficiency; Cost function; Data visualization; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Knowledge engineering; Power engineering and energy; categorical; fuzzy; hybrid; self-organizing map;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on

Conference_Location

Shandong

Print_ISBN

978-0-7695-3305-6

Type

conf

DOI

10.1109/FSKD.2008.149

Filename

4665944