SVM Feature Selection and Sample Regression for Chinese Medicine Research

摘要：

In this paper,SVM based feature selection meth- ods are introduced for regression problem of COX2 inhibitor activity prediction in Chinese medicine Quantitative Structure- Activity Relationship (QSAR)research.We develop a recursive SVM feature selection algorithm for regression and compare its performance with Genetic Algorithm and SVM Recursive Feature Elimination (SVM-RFE)algorithm.Experiments on real Chinese medicine dataset show that our method is a fast and accurate algorithm for Chinese medicine regression problem with a small number of samples.

作者: Wei Li Yannan Zhao Yixu Song Zehong Yang

作者单位: Tsinghua National Laboratory of Information Science and Technology Department of Computer Science,Tsinghua University 100084,Beijing,China

会议类型: 国际会议

会议名称: 2008 IEEE International Conference on Onformation and Automation(IEEE 信息与自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 1773-1777

在线出版日期: 2008-06-20（万方平台首次上网日期，不代表论文的发表时间）