| 基于特征点选择的聚类算法研究 |
| |
| 引用本文： | 朱国红,石冰,邢晓娜.基于特征点选择的聚类算法研究[J].山东大学学报(理学版),2009,44(9):40-42. |
| |
| 作者姓名： | 朱国红 石冰 邢晓娜 |
| |
| 作者单位： | 山东大学计算机科学与技术学院;河南城建学院; |
| |
| 摘 要： | 针对当前数据挖掘中对数值型数据聚类方法的不足,提出了基于特征点选择的聚类算法(clustering algorithm based on Feature Point Selection,CFPS)。CFPS算法可以克服需要输入聚类数量的缺陷, 算法本身可以找到簇的最佳数量,使聚类的精度和效率得到大大提高。实验结果表明该方法对数值型数据聚类方法具有借鉴意义和深入研究的价值。
|
| 关 键 词： | 聚类 k均值 数据挖掘 |
| 收稿时间： | 2009-05-20 |
A clustering algorithm based on feature point selection |
| |
| ZHU Guo-hong,SHI Bing,XING Xiao-na.A clustering algorithm based on feature point selection[J].Journal of Shandong University,2009,44(9):40-42. |
| |
| Authors: | ZHU Guo-hong SHI Bing XING Xiao-na |
| |
| Affiliation: | 1.School of Computer Science and Technology;Shandong University;Jinan 250101;Shandong;China;2.Henan University of Urban Construction;Pingdingshan 467044;Henan;China |
| |
| Abstract: | A clustering algorithm based on Feature Point Selection in Data Mining(abbreviated CFPS) is put forward in this pa-per.This method can overcome the disadvantage of a algorithm which requires the number of clusters for numerical incoming da-ta.The CFPS algorithm finds the optimal number of clusters,and greatly improves the precision and efficiency of clustering.The results of experiments prove that using the algorithm for the numerical data clustering method is feasible,which is valuable for fur-ther study i... |
| |
| Keywords: | clustering k-means data mining |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《山东大学学报(理学版)》浏览原始摘要信息 |
|
点击此处可从《山东大学学报(理学版)》下载全文 |
