计算机工程与应用2011，Vol.47Issue(35)：132-134,3.DOI:10.3778/j.issn.1002-8331.2011.35.037
一种新的k-means聚类中心选取算法
New k-means clustering center select algorithm
摘要
Abstract
A part of the existing algorithm is improved.Through computing the distance between data object to count the density parameter of every data object, the biggest density parameter data objects are chosen as the initial clustering centers. When more than one biggest density parameter,the solution how to select the biggest density parameter is proposed,k initial clustering centers are found.And a new k-means clustering center algorithm is proposed.The experimental result proves the improved algorithm can get higher accuracy.关键词
k-means算法/聚类中心/密度参数Key words
k-means algorithm/clustering center/density parameter分类
信息技术与安全科学引用本文复制引用
黄敏,何中市,邢欣来,陈英..一种新的k-means聚类中心选取算法[J].计算机工程与应用,2011,47(35):132-134,3.基金项目
国家科技重大专项基金(No.2008ZX07315-001). （No.2008ZX07315-001）
