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International Conference on Computer Research and Development, 5th (ICCRD 2013)

Fan Yama
Fan Yama
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ASME Press
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Fuzzy C-means (FCM) clustering algorithm is a typical representative of the fuzzy clustering methods which are based on the objective functions in clustering algorithms. So far, a lot of literatures still have been studying the fuzzy clustering algorithms which are based on the objective functions. In order to understand these clustering algorithms and their characteristics more systematically and deeply, this paper reviews and evaluates advantages and disadvantages of each typical fuzzy C-means algorithm from three aspects: the modification of the objective function, the modification of degree of membership constraints and clustering problems of different types of data, and summarizes the prevalent problems among the improved fuzzy C-means clustering algorithms improved fuzzy C-means clustering algorithms and prospects of them.

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