Skip to Main Content
ASME Press Select Proceedings

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

Editor
Fan Yama
Fan Yama
Search for other works by this author on:
ISBN:
9780791860182
No. of Pages:
278
Publisher:
ASME Press
Publication date:
2013

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.

You do not currently have access to this chapter.
Close Modal
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close Modal
Close Modal