计算机工程与应用2013，Vol.49Issue(2)：157-159,3.DOI:10.3778/j.issn.1002-8331.1106-0299
改进的层次K均值聚类算法
Improved hierarchical K-means clustering algorithm
胡伟1
作者信息
- 1. 山西财经大学实验教学中心,太原030006
- 折叠
摘要
Abstract
This paper presents an improved hierarchical K-means clustering algorithm combining hierarchical structure of space, in order to solve the problem that bad result of traditional K-means clustering method by selecting the number of categories randomly before clustering. By primary A-means clustering, it determines whether re-clustering in the more fine level by the result of initial clustering. By repeated execution, a hierarchical K-means clustering tree is produced, and the number of clusters is selected automatically on this tree structure. Simulation results on UCI datasets demonstrate that comparing with traditional AT-means clustering means, the better clustering results are obtained by the hierarchical K-means clustering model.关键词
K均值聚类/聚类个数/层次结构/层次K均值聚类算法/聚类树Key words
K-means clustering/ clustering number/ hierarchical structure/ hierarchical K-means algorithm/ clustering tree分类
信息技术与安全科学引用本文复制引用
胡伟..改进的层次K均值聚类算法[J].计算机工程与应用,2013,49(2):157-159,3.
