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一种隶属关系不确定的可能性模糊聚类方法
引用本文:陈健美,陆虎,宋余庆,宋顺林,徐景,谢从华,倪巍伟.一种隶属关系不确定的可能性模糊聚类方法[J].计算机研究与发展,2008,45(9).
作者姓名:陈健美  陆虎  宋余庆  宋顺林  徐景  谢从华  倪巍伟
作者单位:1. 江苏大学计算机与通信工程学院,江苏镇江,212013
2. 南京理工大学计算机科学与技术学院,南京,210094
3. 常熟理工学院计算机科学与工程学院,江苏常熟,215500
4. 东南大学计算机科学与工程学院,南京,210096
基金项目:国家自然科学基金,江苏省软件与集成电路专项基金
摘    要:模糊聚类是聚类分析的一个重要分支,模糊C-均值聚类算法及其改进算法都是一种基于概率约束的聚类方法,所采用隶属度的取值形式体现了数据集的绝对隶属程度,常常出现不理想的聚类结果.对此,提出了不确定隶属的概念,在此基础上,通过提出两个基于相对隶属程度的判断准则参数,设计出一种新的基于隶属关系不确定的可能性模糊聚类新算法,并给出了具体算法实现.新算法将迭代过程中数据集对聚类簇隶属的可能性与不确定性关系引入目标函数中,达到明显的优化聚类结果的功效.理论分析和实验结果表明,相对其他聚类算法,新算法具有更高的聚类正确率.

关 键 词:模糊聚类  不确定隶属关系  可能性隶属度  不确定性隶属度  聚类算法

A Possibility Fuzzy Clustering Algorithm Based on the Uncertainty Membership
Chen Jianmei,Lu Hu,Song Yuqing,Song Shunlin,Xu Jing,Xie Conghua,Ni Weiwei.A Possibility Fuzzy Clustering Algorithm Based on the Uncertainty Membership[J].Journal of Computer Research and Development,2008,45(9).
Authors:Chen Jianmei  Lu Hu  Song Yuqing  Song Shunlin  Xu Jing  Xie Conghua  Ni Weiwei
Affiliation:Chen Jianmei1,Lu Hu1,Song Yuqing1,Song Shunlin1,Xu Jing2,Xie Conghua3,, Ni Weiwei41(School of Computer Science , Telecommunications Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013)2(School of Computer Science , Technology,Nanjing University of Science , Technology,Nanjing 210094)3(School of Computer Science , Engineering,Changshu Institute of Technology,Changshu,Jiangsu 215500)4(School of Computer Science , Engineering,Southeast University,Nanjing 210096)
Abstract:Clustering, as an unsupervised learning method, is a hot topic in data mining and has been widely used. Fuzzy clustering is an important branch of clustering. Many representative fuzzy clustering algorithms have been proposed, such as fuzzy c-means. Fuzzy c-means clustering algorithm and its improved versions are absolutely probability constrained clustering algorithms, which adapt the membership forms that represent the absolutely subordinative extent of the data. Some complex data distribution would make ...
Keywords:fuzzy clustering  uncertainty membership relationship  possibility membership degree  uncertainty membership degree  clustering algorithm  
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