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Fuzzy Clustering Approaches Based on AFS Fuzzy Logic I

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3 Author(s)
Yan Ren ; Dept. of Math., Dalian Maritime Univ. ; Xianchang Wang ; Xiaodong Liu

In this paper, the AFS fuzzy logic clustering algorithm (X.D. Liu, W. Wang and T.Y. Chai, IEEE Transaction on Systems, Man, Cybernetics, 2005) have be studied further by the improvement of the algorithm and the application of the algorithm to iris data (reference ftp://ftp.ics.uci.edu/pub/machine-learning-databases/Iris/). In stead of examples of less than 10 samples, we apply the improved algorithm to iris data which has 150 samples and just the order relationship of the samples on the attributes are used. This study shows that the AFS fuzzy logic clustering algorithm can obtain a high reclassification accuracy according to the order relationship. Thus the algorithm can be applied to the data sets in which the attributes are only described by order relationship

Published in:

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on  (Volume:1 )

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