%0 Journal Article
%T Initial Cluster Centers Choice Algorithm for K-means Based on Neighborhood Model<br>基于邻域模型的K-means初始聚类中心选择算法
%A CAO Fu-yuan
%A LIANG Ji-ye
%A JIANG Guang
%A <br>曹付元
%A 梁吉业
%A 姜广
%J 计算机科学
%D 2008
%I 
%X The traditional K-means algorithm considered as a simple method has been widely discussed and applied in pattern recognition and machine learning.However,K-means algorithm can not guarantee unique clustering result because initial cluster centers are chosen randomly,moreover,choosing initial cluster centers is extremely important as it has a direct impact on the formation of final clusters.In this paper,concepts of coupling and division are defined by using low approximation and upper approximation of objec...
%K Neighborhood model
%K Initial cluster centers
%K K-means clustering
%K Rough set<br>邻域模型
%K 初始聚类中心
%K K-means聚类
%K 粗糙集
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=D471C8F5E0950E19ABC70075C02EB4E6&yid=67289AFF6305E306&vid=6209D9E8050195F5&iid=708DD6B15D2464E8&sid=7EBE588F611589FC&eid=798FBE8DE1A255B1&journal_id=1002-137X&journal_name=计算机科学&referenced_num=2&reference_num=18