A Weighting Fuzzy Clustering Algorithm Based on Euclidean Distance

Authors:
Zhan-ao Xue;Feng Cen;Li-ping Wei
Affiliations:
-;-;-
Venue:
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
Year:
2008

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Abstract

Considering a user's actual demand, this paper analyzed the functional requirments which can be brought forward by a user of a clustering system and proposed a fuzzy c-means clustering algorithm based on Euclidean distance. In this algorithm, weights are directly appointed by a user or a domanial expert. Different weights show the distinction of the user’s recognition of different character criterion. Compared with the traditional Fuzzy c-means clustering method, this algorithm can improve the clustering’s flexibility and produce a more satisfactory clustering result.