Affiliations: [a] Department of Business Administration, National Central University, Taoyuan City, Taiwan | [b] Faculty of Economics, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam
Correspondence:
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Corresponding author: Phan-Anh-Huy Nguyen, Faculty of Economics, Ho Chi Minh City University of Technology and Education, No. 1, Vo Van Ngan Rd, Thu Duc Dist, Ho Chi Minh City, Vietnam. E-mail: [email protected].
Abstract: One main problem of Fuzzy c-Means (FCM) is deciding on an appropriate number of clusters. Although methods have been proposed to address this, they all require clustering algorithms to be executed several times before the right number is chosen. The aim of this study was to develop a method for determining cluster numbers without repeated execution. We propose a new method that combines FCM and singular value decomposition. Based on the percentage of variance, this method can calculate the appropriate number of clusters. The proposed method was applied to several well-known datasets to demonstrate its effectiveness.
Keywords: Fuzzy c-Means (FCM), clustering, singular value decomposition, number of clusters, processing time
