1.Laboratory of Image Information Processing, School of Computer and Information, Hefei University of Technology, Hefei 230009 2.Center of Biomimetic Sensing and Control Research, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031
Abstract：Clustering is considered as the most important problem of unsupervised learning. A Hierarchical Fuzzy MinMax Clustering Algorithm (HFMM) is presented based on the original Fuzzy MinMax Clustering Neural Network (FMMCN) and hierarchical clustering. Compared with the existing methods for clustering, the proposed algorithm dynamically determines the number of clusters to meet the demands of the problem. Moreover it overcomes the shortcomings of FMMCNorder dependent. Experimental results on three databases demonstrate that HFMM has high clustering performance.
[1] MacQueen J B. Some Methods for Classification and Analysis of Multivariate Observations // Proc of the 5th Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, USA, 1967, Ⅰ: 281297 [2] Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms. New York, USA: Plenum Press, 1981 [3] Bhatia S K. Adaptive KMeans Clustering // Proc of the 17th International Florida Artificial Intelligence Research Society Conference. Miami Beach, USA, 2004: 695699 [4] Gao Jian. Cluster Analysis Based on CMeans and Immune Genetic Algorithm. Computer Engineering, 2003, 29(12): 6566,194 (in Chinese) (高 坚.基于C均值和免疫遗传算法的聚类分析.计算机工程, 2003, 29(12): 6566,194) [5] Zhang Li, Zhou Weida, Jiao Licheng. Kernel Clustering Algorithm. Chinese Journal of Computers, 2002, 25(6): 587590 (in Chinese) (张 莉, 周伟达, 焦李成. 核聚类算法. 计算机学报, 2002, 25(6): 587590) [6] Hu Yusuo, Chen Zonghai. Cluster Analysis Based on Hybrid Genetic Algorithms. Pattern Recognition and Artificial Intelligence, 2001, 14(3): 352355 (in Chinese) (胡玉锁, 陈宗海. 基于混合遗传算法的聚类分析. 模式识别与人工智能, 2001, 14(3): 352355) [7] Simpson P K. Fuzzy MinMax Neural Networks-Part 2: Clustering. IEEE Trans on Fuzzy Systems, 1993, 1(1): 3245 [8] Huang Xiaobin, Ma Xiaoyan, Chen Song, et al. A Novel Fuzzy MinMax Clustering Algorithm Based on Group Fusion. Computer Engineering and Design, 2002, 23(11): 7881,85 (in Chinese) (黄晓斌,马晓岩,陈 松,等.一种基于类别融合的模糊最小最大聚类算法.计算机工程与设计, 2002, 23(11): 7881,85) [9] Deng Zhaohong, Wang Shitong. Robust Fuzzy Clustering Neural Networks. Journal of Software, 2005, 16(8): 14151422 (in Chinese) (邓赵红, 王士同. 鲁棒性的模糊聚类神经网络. 软件学报, 2005, 16(8): 14151422) [10] Huang Xiaobin, Ma Xiaoyan, Peng Zhigang. A Novel Clustering Algorithm Based on Rotated SuperBox. Systems Engineering-Theory & Practice, 2003, 23(5): 113116 (in Chinese) (黄晓斌, 马晓岩, 彭志刚. 一种基于旋转最小最大超盒的聚类算法. 系统工程理论与实践, 2003, 23(5): 113116) [11] Johnson S C. Hierarchical Clustering Schemes. Psychometrika, 1967, 32(3): 241254 [12] Gabrys B, Bargiela A. General Fuzzy MinMax Neural Network for Clustering and Classification. IEEE Trans on Neural Networks, 2000, 11(3): 769783 [13] Hattori K, Takahashi M. A New Edited kNearest Neighbor Rule in the Pattern Classification Problem. Pattern Recognition, 2000, 33(3): 521528
2007, Vol. 20 
