| 一种基于广度优先搜索的K-means初始化算法 |
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| 引用本文： | 张忠平,王爱杰,陈丽萍.一种基于广度优先搜索的K-means初始化算法[J].计算机工程与应用,2008,44(27):159-161. |
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| 作者姓名： | 张忠平 王爱杰 陈丽萍 |
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| 作者单位： | 燕山大学 信息科学与工程学院，河北 秦皇岛 066004 |
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| 基金项目： | 教育部科学技术研究重点项目，河北省教育厅科研项目 |
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| 摘 要： | K-means算法是在现实应用中非常广泛的聚类算法，K-means算法对初始中心的选择非常敏感，对已存在的有代表性的初始算法进行了研究，提出了一种基于广度优先搜索的K-means初始化算法。该算法综合考虑了密度与距离因素，选择初始点。分析表明该算法选择的初始点非常接近期望的中心点。
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| 关 键 词： | K-means算法 广度优先搜索 密度估计 初始化 |
| 收稿时间： | 2007-11-9 |
| 修稿时间： | 2008-1-31
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Method for initializing K-means clustering algorithm based on breadth first search |
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| ZHANG Zhong-ping,WANG Ai-jie,CHEN Li-ping.Method for initializing K-means clustering algorithm based on breadth first search[J].Computer Engineering and Applications,2008,44(27):159-161. |
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| Authors: | ZHANG Zhong-ping WANG Ai-jie CHEN Li-ping |
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| Affiliation: | College of Information Science and Engineering，Yanshan University，Qinhuangdao，Hebei 066004，China |
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| Abstract: | K-means algorithm is a clustering algorithm used extensively in application.It is very sensitive to initial cluster center.In this paper,the authors compare some classic initialization algorithm and propose a new method for initializing K-means algorithm based on breadth first search.The new method considers both density estimation and distance to select initial cluster center.Analysis shows the cluster centers selected by this method is very close to the desired cluster centers. |
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| Keywords: | K-means breadth first search density estimation initialization |
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