@article{(Open Science Index):https://publications.waset.org/pdf/13160,
	  title     = {Parameter Selections of Fuzzy C-Means Based on Robust Analysis},
	  author    = {Kuo-Lung Wu},
	  country	= {},
	  institution	= {},
	  abstract     = {The weighting exponent m is called the fuzzifier that
can have influence on the clustering performance of fuzzy c-means
(FCM) and mÎ[1.5,2.5] is suggested by Pal and Bezdek [13]. In this
paper, we will discuss the robust properties of FCM and show that the
parameter m will have influence on the robustness of FCM. According
to our analysis, we find that a large m value will make FCM more
robust to noise and outliers. However, if m is larger than the theoretical
upper bound proposed by Yu et al. [14], the sample mean will become
the unique optimizer. Here, we suggest to implement the FCM
algorithm with mÎ[1.5,4] under the restriction when m is smaller
than the theoretical upper bound.},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {4},
	  number    = {5},
	  year      = {2010},
	  pages     = {558 - 561},
	  ee        = {https://publications.waset.org/pdf/13160},
	  url   	= {https://publications.waset.org/vol/41},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 41, 2010},
	}