Partial least squares variable selection method and its application in drug source analysis

Abstract

A novel variable selection method has been proposed. In this method some information in PLS modeling has been used to select original regression variables, to eliminate some unimportant or uninformative variables and to obtain the more simple and optimal prediction model. Comparing with the results from the traditional methods using this method as well as the expansion of variable dimension to deal with the data included 244 heroin samples by ICP-MS from three sources i. e. Kunming, Simao and Xishuangbanna in Yunnan province, the discrimination accuracy of model increase greatly and over 95%. Because the obtained model contains few variables, it is easy to analysis or explains the variables effect to the model. Hence the method can be used to discriminate or determine the drug sources effectively.