Comparative study of two uncertain support vector machines

Abstract

In order to overcome the problem that it is difficult for support vector machine to deal with uncertain information system, fuzzy theory and rough set are introduced to get two uncertain support vector machines, which are fuzzy support vector machine and fuzzy rough support vector machine respectively. And the principle of these two uncertain methods reducing the effect of uncertain information is explained, comparative analysis between fuzzy support vector machine and fuzzy rough support vector machine is done. At last several comparative experiments using synthetic and real life data set show that theses two uncertain methods have a better performance and significantly improve the classification accuracy.