%0 Journal Article
%T Research about transferred feature selection based on GMDH<br>基于GMDH的迁移特征选择模型研究*
%A LI Hong-mei
%A HE Chang-zheng
%A XIAO Jin
%A <br>李红梅
%A 贺昌政
%A 肖进
%J 计算机应用研究
%D 2012
%I 
%X This paper proposed a transferred feature selection model based on group method of data handling (GMDH-TFS) by integrating transfer learning and the group method of data handling algorithm. Comparison on four data sets of UCI among GMDH-TFS, classification with full features(FULL), supervised forward feature selection (SFFS), forward semi-supervised feature selection(FW-SemiFS) and transferred feature selection(TFS) show that GMDH-TFS has a better performance than other methods as well as in the case of learning with small samples. GMDH-TFS can do feature selection when the data are under different distribution, and can get satisfactory results even the data are not enough.
%K feature selection
%K transfer learning
%K group method of data handling(GMDH)<br>特征选择
%K 迁移学习
%K 数据分组处理
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F950C016BC33E90184BDEE56BF6F94A6&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=38B194292C032A66&sid=C81F81170838C444&eid=AB1DE136C335A86C&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=15