| 数据聚类算法的改进及其应用 |
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| 引用本文： | 席泓.数据聚类算法的改进及其应用[J].电脑开发与应用,2006,19(11):7-8. |
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| 作者姓名： | 席泓 |
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| 作者单位： | 贵州民族学院数学与计算机科学学院,贵阳,550025 |
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| 基金项目： | 贵州民族学院校科研和教改项目 |
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| 摘 要： | 在分析和比较k平均分区算法和层次凝聚算法的基础上,提出了一种新的改进算法(NQ算法)。并以贵州民族学院近四年学生试卷数据作为测试数据,对NQ算法与k平均分区算法和层次凝聚算法进行了性能对比,实践证明:NQ算法是有效、可靠和快速的。
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| 关 键 词： | k平均分区算法 层次凝聚算法 改进 试卷数据分析 |
| 文章编号： | 1003-5850（2006）11-0007-02 |
| 收稿时间： | 2006-06-26 |
| 修稿时间： | 2006-09-08 |
Improvement and Application of Data Clustering Algorithm |
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| Xi Hong.Improvement and Application of Data Clustering Algorithm[J].Computer Development & Applications,2006,19(11):7-8. |
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| Authors: | Xi Hong |
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| Abstract: | The paper analyses and compares the different disadvantages of k mean partition algorithm and layer clustering algorithm and then points out an improved new algorithm(NQ algorithm).The NQ algorithm,k mean partition algorithm and layer clustering algorithm are compared in performance by means of the analysis of test paper in Guizhou Nationality College during resent four years.The result shows that NQ algorithm is quicker and more effective than the other two methods. |
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| Keywords: | k mean partition algorithm layer clustering algorithm improvement analysis of test paper data |
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