| 熵指数约束的模糊聚类新算法 |
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| 引用本文： | 黄成泉, 王士同, 蒋亦樟. 熵指数约束的模糊聚类新算法[J]. 计算机研究与发展, 2014, 51(9): 2117-2129. DOI: 10.7544/issn1000-1239.2014.20130305 |
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| 作者姓名： | 黄成泉 王士同 蒋亦樟 |
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| 作者单位： | 1.1(江南大学数字媒体学院 江苏无锡 214122);2.2(贵州民族大学理学院 贵阳 550025) (hcq863@163.com) |
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| 基金项目： | 国家自然科学基金项目，江苏省自然科学基金项目，贵州省科学技术基金项目 |
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| 摘 要： | 针对基于模糊C均值聚类(fuzzy C-means, FCM)算法框架的竞争聚集聚类(competitive agglomeration, CA)算法中模糊指数m被限定为2的问题,提出了一种更为普适的模糊聚类新算法.该算法首先在FCM算法框架的基础上引入熵指数约束条件，构造了基于熵指数约束的模糊C均值聚类(entropy index constraint FCM, EIC-FCM)算法，成功地将模糊指数m>1的约束条件转换为熵指数0
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| 关 键 词： | 竞争聚集 模糊指数 熵指数 熵指数约束 模糊聚类 |
A New Fuzzy Clustering Algorithm with Entropy Index Constraint |
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| Huang Chengquan, Wang Shitong, Jiang Yizhang. A New Fuzzy Clustering Algorithm with Entropy Index Constraint[J]. Journal of Computer Research and Development, 2014, 51(9): 2117-2129. DOI: 10.7544/issn1000-1239.2014.20130305 |
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| Authors: | Huang Chengquan Wang Shitong Jiang Yizhang |
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| Affiliation: | 1.1(School of Digital Media, Jiangnan University, Wuxi, Jiangsu 214122);2.2(School of Science, Guizhou Minzu Univeristy, Guiyang 550025) |
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| Abstract: | The fuzziness index m plays an important role in the clustering result of fuzzy clustering algorithms. In order to avoid the fuzziness index m of the CA (competitive agglomeration) clustering algorithm based on FCM (fuzzy C-means) clustering algorithm framework being forced to fix at the usual value 2, a more universal fuzzy clustering algorithm is proposed. Firstly, a fuzzy clustering algorithm named EIC-FCM (entropy index constraint FCM), which has comparable clustering performance to the classical FCM algorithm, is presented by introducing an entropy index r into constraints with m=1. The successful introducing of entropy index r effectively makes the fuzziness index constraint m>1 transform into entropy index constraint 0
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| Keywords: | competitive agglomeration fuzziness index entropy index entropy index constraint fuzzy clustering |
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