Indices Selection for SVC Early Warning System

摘要

Support vector classification (SVC) is a powerful classification technique and has been successfully applied to many real-world problems. In this paper, a new economic warning indices selection method is proposed for SVC early warning system for the first time. The method is based upon finding minimize those indices which bounds on the leaver-one-out error (loo). This search can be efficiently performed via Newton's method. Moreover, early warning indices selection of China grain security is solved by our resulting algorithm.