太原理工大学学报2012，Vol.43Issue(2)：114-118,5.
基于2d-距离改进的K-means聚类算法研究
Research on improved K-means Clustering Algorithm Based on Two-distance
摘要
Abstract
In order to overcome the shortcoming of original K-means algorithm that randomly selecting clustering center puts much influence on clustering results,prevent the destruction on clustering precision resulted from the existance of isolated points,and reveal the inter relationship between them, this paper adopted DKC value of 2d-distance to pretreat original sample data to distingwish isolated points and determine initial clustering center,so as to eliminater the interrelationship and stablize clustering center. Compared with original algorithm, the improved one is more effective in accuracy.关键词
2d-距离/K-means算法/初始点选取/孤立点Key words
2d-distance/ K-means algorithm/ the selection of primitive center/ isolated point分类
信息技术与安全科学引用本文复制引用
陈福集,蒋芳..基于2d-距离改进的K-means聚类算法研究[J].太原理工大学学报,2012,43(2):114-118,5.基金项目
国家杰出青年科学基金(70925004) （70925004）
