@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}, }