%0 Journal Article
%T P-SVM Applications in TCM Syndrome Classifications<br>支持向量机算法在中医证候信息分类中的应用
%A Yang Xiaobo
%A Liang Zhaohui
%A Luo Yunjian
%A Chen Ling
%A <br>杨小波
%A 梁兆晖
%A 罗云坚
%A 陈 玲
%J 世界科学技术-中医药现代化
%D 2007
%I 
%X The paper explores possible applications of Prior knowledge Support Vector Machine (P-SVM) based data mining algorithm in an automatic TCM syndrome classification system. In the study, a TCM syndrome database containing some 300,000 medical records is used as a sample set for algorithm training and test. In addition, a range of TCM syndrome theories are incorporated into a prior knowledge set. The sample set is made part of the SVM model, with weighted sequence for classification. The confidence value for each result is also calculated on an individualized basis. It is proved that with prior TCM knowledge, the accuracy of the automatic TCM syndrome classification system can be raised to a level as high as 95%. It is concluded that P-SVM has made a successful application of statistical learning theory (SLT) to the given samples, though limited in number, which heralds an effective approach for improving automatic TCM syndrome classification, and proves the applicab e features of datamining in TCM syndrome researches. The results show that P-SVM marries prior knowledge with the trained samples, and it is an effective a lgorithm for TCM syndrome classification.
%K TCM Syndrome
%K data mining
%K information technology
%K support vector machine<br>中医证候
%K 数据挖掘
%K 信息技术
%K 支持向量机
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=A9DB1C13C87CE289EA38239A9433C9DC&cid=B5F35A1FC27C1FF7&jid=44257A35316DB0727BA6BC707B9EDAAB&aid=29C0764AAC1C331FCED13506591057CE&yid=A732AF04DDA03BB3&vid=9CF7A0430CBB2DFD&iid=CA4FD0336C81A37A&sid=D3E34374A0D77D7F&eid=4AD960B5AD2D111A&journal_id=1674-3849&journal_name=世界科学技术-中医药现代化&referenced_num=0&reference_num=0