CSVM and Its Application in the Chinese Theme Classification

作     者：WANG Guang School of software LIAONING Technical University Huludao,China QIU Yun-fei,LI Hong-xia School of software LIAONING Technical University Huludao,China 

会议名称：《2010 International Conference on Optics, Photonics and Energy Engineering (OPEE 2010)》

会议日期：2010年

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by Youth Fond of LIAONING TECHNICAL UNIVERSITY 

关 键 词：Chinese Theme Classification SVM Adaboost MEB. 

摘      要：Support vector machine has been widely used in the classification *** 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 *** 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.