| Bezdek型模糊属性C均值聚类算法 |
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| 引用本文： | 刘敬伟,徐美芝.Bezdek型模糊属性C均值聚类算法[J].北京航空航天大学学报,2007,33(9):1121-1126. |
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| 作者姓名： | 刘敬伟 徐美芝 |
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| 作者单位： | 北京航空航天大学,理学院,北京,100083;清华大学数学科学系,北京,100084 |
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| 摘 要： | 推广了属性均值聚类算法,提出了基于模糊度m的Bezdek型模糊属性C均值聚类算法(FAMC),给出了FAMC算法的迭代算法,并讨论了模糊度m对算法收敛性的影响.在标准Iris数据集与肿瘤基因芯片表达数据的模式识别实验结果,验证了该算法优于模糊C均值算法和属性均值聚类算法.
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| 关 键 词： | 模糊C均值聚类算法 属性均值聚类 稳态函数 基因表达数据 |
| 文章编号： | 1001-5965（2007）09-1121-06 |
| 收稿时间： | 2006-08-23 |
| 修稿时间： | 2006-08-23 |
Bezdek type fuzzy attribute C-means clustering algorithm |
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| Liu Jingwei,Xu Meizhi.Bezdek type fuzzy attribute C-means clustering algorithm[J].Journal of Beijing University of Aeronautics and Astronautics,2007,33(9):1121-1126. |
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| Authors: | Liu Jingwei Xu Meizhi |
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| Institution: | 1. School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
2. Department of Mathematical Sciences, Tsinghua University, Beijing, 100084 |
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| Abstract: | Bezdek type fuzzy attribute C-means clustering algorithm(FAMC) was proposed by extending attribute means clustering(AMC) algorithm based on fuzziness index(or weighting exponent) m.The iterative algorithm was derived and the effect of fuzziness index m on objective function convergence was discussed.The experimental results of pattern recognition performances on standard Iris database and tumor/normal gene chip expression data demonstrate that FAMC is more effective than fuzzy C-means clustering(FCM) algorithm and AMC. |
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| Keywords: | fuzzy C-means clustering attribute means clustering stable function gene expression data |
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