%0 Journal Article
%T Modified KNN algorithm for multi-label learning<br>用于多标记学习的K近邻改进算法*
%A ZHANG Shun
%A ZHANG Hua-xiang
%A <br>张顺
%A 张化祥
%J 计算机应用研究
%D 2011
%I 
%X ML-KNN is an approach that employs KNN to solve multi-label problems,but it suffers from the problems of high time complexity and low classification accuracy.This paper proposed a modified algorithm WML-KNN to solve these problems.It combined data sampling and weighting into one approach,and resulted in the time complexity reduction and the classification accuracy improvement of the minority class data.Experimental results show that WML-KNN works better than other commonly used multi-label algorithms.
%K classification
%K KNN
%K sampling
%K multi-label learning<br>分类
%K K近邻
%K 取样
%K 多标记学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=FB5801A5F05F25BDA106548EE90D07C1&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=59906B3B2830C2C5&sid=462AB175E297D285&eid=9833A977204866B9&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=14