%0 Journal Article
%T Iterative Learning Assignment Order for Constrained K-means Algorithm<br>面向限制K-means算法的迭代学习分配次序策略
%A QIU Ye
%A HE Zhen-feng
%A <br>邱 烨
%A 何振峰
%J 计算机科学
%D 2012
%I 
%X Constrained K-means algorithm often improves clustering accuracy, but sensitive to the assignment order of instances. A clustering uncertainty based assignment order Iterative Learning Algorithm(UALA) was proposed to gain a good assignment order. The instances stability was gradually confirmed by iterative thought according to the characteristics of Cop-Kmeans algorithm stability, and then assignment order was confirmed. The experiment demonstrates that the algorithm effectively improves the accuracy of Cop-Kmeans algorithm.
%K Clustering analysis
%K Semi-supervise clustering
%K K-means
%K Instancelevel constraints<br>聚类分析
%K 半监督聚类
%K K-means
%K 关联限制
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=FDABA0B07E06BAF84489A5EB80CEC951&yid=99E9153A83D4CB11&vid=7C3A4C1EE6A45749&iid=5D311CA918CA9A03&sid=E0F6F365E4766526&eid=284EBBCC4532AEDD&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0