| 空间聚类算法中的K值优化问题研究 |
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| 引用本文： | 李永森,杨善林,马溪骏,胡笑旋,陈增明.空间聚类算法中的K值优化问题研究[J].系统仿真学报,2006,18(3):573-576. |
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| 作者姓名： | 李永森 杨善林 马溪骏 胡笑旋 陈增明 |
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| 作者单位： | 合肥工业大学计算机网络系统研究所,合肥,230009 |
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| 摘 要： | 在典型的空间聚类算法K-平均法和K-中心法中,K一般为用户事先确定的值,然而,实际中K值很难被精确地确定,往往表现为一个模糊的取值区间。在此提出距离代价函数的概念,建立了相应的数学模型并设计了一个新的K值优化算法,对空间聚类K值优化问题进行了初步的研究。
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| 关 键 词： | 空间聚类 K-平均算法 距离代价函数 K值优化 |
| 文章编号： | 1004-731X（2006）03-0573-04 |
| 收稿时间： | 2005-01-12 |
| 修稿时间： | 2005-11-29 |
Optimization Study on K Value of Spatial Clustering |
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| LI Yong-sen,YANG Shan-lin,MA Xi-jun,HU Xiao-xuan,CHEN Zeng-ming.Optimization Study on K Value of Spatial Clustering[J].Journal of System Simulation,2006,18(3):573-576. |
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| Authors: | LI Yong-sen YANG Shan-lin MA Xi-jun HU Xiao-xuan CHEN Zeng-ming |
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| Institution: | Institute of Computer Network System, Hefei University of Technology, Hefei 230009, China |
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| Abstract: | The value of K is always confirmed in advance to exert K-means algorithm of spatial clustering.However,it can not be clearly and easily confirmed in fact for its uncertainty.A distance cost function was recommended.A corresponding math model was set up and a new optimization algorithm of K value was designed.A preliminary study on the optimization of K value for spatial clustering was realized by a simulation design. |
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| Keywords: | spatial clustering K-means algorithm distance cost function optimization of K |
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