%0 Journal Article
%T Effective selective sampling with dynamic certainty propagation<br>基于动态确定度传播的选择性采样
%A ZHANG Xiao-yu
%A <br>张晓宇
%J 计算机应用研究
%D 2012
%I 
%X In traditional active learning, selective sampling was performed in batch mode, which neglected examples' correlation and thus inevitably brought in redundancy. This paper presented a dynamic batch sampling mode, using both the existing classification boundary and the previously labeled examples as guidance for further selection. Then it proposed a dynamic certainty propagation(DCP)algorithm for informative example selection. Experimental results demonstrate the effectiveness of selective sampling with DCP algorithm.
%K relevance feedback
%K semi-supervised learning
%K active learning
%K multi-view learning
%K selective sampling<br>相关反馈
%K 半监督学习
%K 主动学习
%K 多视角学习
%K 选择性采样
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F886A295C1E57CC56332A15175374A24&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=94C357A881DFC066&sid=1B889749E306CF0E&eid=EECD17CB3E221F65&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=17