SVM feature selection and sample regression for Chinese medicine research
Wei Li, Yannan Zhao, Yixu Song, Zehong Yang · 2008
In this paper, SVM based feature selection methods 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.