Research of support vector classification based on rough set

The basic concept of rough set(RS)and principle of support vector machines(SVM)are introduced,and the combination of RS and SVM is presented.Redundant attributes and conflicting objects are deleted from decision making table by using the attribute reduction of RS.The structure of the SVM classifiers is simplified and the classification efficiency of SVM is improved in terms of using rough set for data preprocessing.Then experimental result shows the performance of the method.