%0 Journal Article
%T Study on Evaluating Data Classifying Quality Based on Mutual Subsethood<br>基于互包含度的数据分类效果评价研究
%A WU Cheng-Mao
%A FAN Jiu-Lun
%A <br>吴成茂
%A 范九伦
%J 计算机科学
%D 2005
%I 
%X Based on the shortage of fuzzy c-means algorithm which initialized classification parameter is sensitivity to data classifying quality,and different initialized classification parameters generate classifying result with bigger other- ness. A new evaluating criterion based on mutual subsethood puts forward to assess data classifying quality in this pa- per. Experimental results show that an evaluating criterion proposed in this paper is feasible.
%K Fuzzy c-means algorithm
%K Mutual subsethood
%K Classifying quality<br>互包含度
%K 数据分类
%K 效果评价
%K 模糊C-均值聚类算法
%K 非监督模式识别方法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=DAC3408AC559D56B&yid=2DD7160C83D0ACED&vid=9971A5E270697F23&iid=CA4FD0336C81A37A&sid=BA79719BCA7341D5&eid=8575BEDA702C4B7C&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=14