%0 Journal Article
%T Novel Autonomous Clustering Method Based on Decision-theoretic Rough Set<br>一种基于决策粗糙集的自动聚类方法
%A YU Hong
%A CHU Shuang-shuang
%A <br>于洪
%A 储双双
%J 计算机科学
%D 2011
%I 
%X This paper proposed an autonomous knowledge-oriented clustering method based on decision-theoretic rough set model. In order to obtain the initial clustering, the initial threshold values need to set in the knowledgcoricnted clustering framework. Thus, a novel method, sort difference, was proposed to produce the initial threshold values autonomously in view of physics theory. Then, a cluster validity index based on the decision-theoretic rough set model was developed by considering various loss functions, which can estimate the quality of clustering.The results of experiments show that the new approach is valuable.
%K Clustering
%K Knowledge-oriented
%K Decision-theoretic rough set
%K Autonomous<br>聚类，面向知识，决策粗糙集，自动
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=82C8F399F8B39871976C97B96FAE115C&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=CA4FD0336C81A37A&sid=78F0EFE028BD3783&eid=A1266CF37D675CF1&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=15