The range of the value for the fuzzifier of the fuzzy c-means algorithm

作     者：Huang, Ming Xia, Zhixun Wang, Hongbo Zeng, Qinghua Wang, Qian 

作者机构：Natl Univ Def Technol Sci & Technol Scramjet Lab Changsha 410073 Hunan Peoples R China Xian Satellite Control Ctr Xian 710043 Peoples R China NW Inst Nucl Technol Xian 710024 Peoples R China 

出 版 物：《PATTERN RECOGNITION LETTERS》 (模式识别快报)

年 卷 期：2012年第33卷第16期

页      面：2280-2284页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China 

主　　题：Fuzzy c-means algorithm Fuzzifier The range of the value The behavior of membership function 

摘      要：The fuzzy c-means algorithm (FCM) is a widely used clustering algorithm. It is well known that the fuzzifier, m, which is also called fuzzy weighting exponent, has a significant impact on the performance of the FCM. Most of the researches have shown that there exists an effective range of the value for m. However, since the method adopted by researchers is mainly experimental or empirical, it is still an open problem how to select an appropriate fuzzifier m in theory when implementing the FCM. In this paper, we propose a theoretical approach to determine the range of the value of m. This approach utilizes the behavior of membership function on two data points, based on which we reveal the partial relationship between the fuzzifier m and the dataset structure. (c) 2012 Elsevier B.V. All rights reserved.