Abstract
Granular support vector machine (GSVM) is a new learning model based on Granular Computing and Statistical Learning Theory. Compared with the traditional SVM, GSVM improves the generalization ability and learning efficiency to a large extent. This paper mainly reviews the research progress of GSVM. Firstly, it analyzes the basic theory and the algorithm thought of GSVM, then tracking describes the research progress of GSVM including the learning model and specific applications in recent years, finally points out the research and development prospects.
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