湖北工程学院学报Issue(6)：21-25,5.
基于局部密度的高效聚类算法研究
Research on Efficient Clustering Algorithm Based on Local Density
周杰 1刘立波 1卜旭松1
作者信息
- 1. 宁夏大学数学计算机学院，宁夏银川750021
- 折叠
摘要
Abstract
In view of the limitation of density -based clustering algorithm that is sensitive to parameter settings and difficult to set the parameters ,this paper proposes an efficient local density -based clus‐tering algorithm for the problem that the density -based clustering algorithm is not accurate to the da‐ta set with different density -levels .The proposed algorithm combines the local density concepts and K -means algorithms and dynamically calculates the local -density parameters and core -distance of the clusters in the process of the iteration . T he data inside the core -distance is clustered into the clusters directly by the partition -based method and the data outside the core distance of the clusters is clustered by the local density method .Experimental results indicate that the proposed method ex‐hibits better performance in both efficiency and accuracy .关键词
k-means/局部密度/簇核心距/聚类Key words
k-means/local density/core-distance/clustering分类
信息技术与安全科学引用本文复制引用
周杰,刘立波,卜旭松..基于局部密度的高效聚类算法研究[J].湖北工程学院学报,2015,(6):21-25,5.
