| 一个基于k-means算法的聚类 |
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| 引用本文： | 陈勇,陈健.一个基于k-means算法的聚类[J].东莞理工学院学报,2010,17(3):27-31. |
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| 作者姓名： | 陈勇 陈健 |
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| 作者单位： | 东莞理工学院,计算机学院,广东东莞,523808 |
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| 摘 要： | 用k-means算法对二维数据进行聚类分析,并用C#语言实现了该算法。先按照样本点的距离进行初始划分,然后再按照各样本点和初始中点的距离远近进行聚类。结果表明,k-means算法对二维数据的聚类是有效的,实现该算法的程序对二维数据的聚类具有通用性。
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| 关 键 词： | k-means算法 聚类 迭代 数据挖掘 |
A Clustering Based on k-Means Algorithm |
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| CHEN Yong,CHEN Jian.A Clustering Based on k-Means Algorithm[J].Journal of Dongguan Institute of Technology,2010,17(3):27-31. |
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| Authors: | CHEN Yong CHEN Jian |
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| Institution: | CHEN Yong CHEN Jian (College of Computer,Dongguan University of Technology,Dongguan 523808,China) |
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| Abstract: | This paper uses k-means algorithm to analyse clusteredly two-dimensional data,and implements the algorithm in C# language.This algorithm makes initial division according to the distance between sample points,and then clusters them based on the distance between each sample point and initial midpoint.The result shows that k-means algorithm is valid to cluster two-dimensional data,and the procedure of the algorithm is applicable for clustering two-dimensional data. |
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| Keywords: | k-means algorithm clustering iterative data mining |
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