Rough classifier based on support vector machine
Sha Shi · Jisuanji gongcheng yu sheji · 2007
Support vector machine(SVM) and rough set(RS) theory are two classification techniques.The former attempts to find an optimal hyperplane that maximize margin between two classes,and the later are designed to provide an explanation of the classification using logical rules.A compact algorithm is proposed based on the relationship between their principles.This new algorithm can reduce the complexity of computation to a certain degree and is especially useful for soft margin classifier;also it is generalized to regression.Numerical results illustrate that the algorithm is feasible and effective.