CSVM and its application in the Chinese theme classification

Support vector machine has been widely used in the classification issues. This paper proposed a new cascade support vector machine classification algorithm CSVM with AdaBoost algorithm framework and support vector machine SVM combination to deal with the problem of multiple classifiers. for the problem of consuming time in the multi-classification problems with support vector machines, this paper introduced the minimum enclosing ball (MEB) algorithm to extract the original sample data to shorten the training time for support vector machines; CSVM was applied in the Chinese theme classification, and the experimental results show that, CSVM algorithm has similar accuracy with AdaBoost algorithm, but the computation time is only 35% of the SVM algorithm¹.