Enrico F,Marco M.Implementing reliable learning through reliable support vector machines [C]//Proceedings 2011 IEEE Symposium on Foundations of Computational Intelligence.Paris:IEEE,2011:100-106
[2]
Zhao Xing,Zhou Yanquan,He Huacan.Researches on algorithm for confidence evaluation and decision modification of SVM [C]// International Conference on Natural Language Processing and Knowledge Engineering.Dalian:NLPKE,2009:1-7
[3]
周皓,李少洪.SVM最优分类面相对位置的修正[J].北京航空航天大学学报,2009,35(11):1302-1305 Zhou Hao,Li Shaohong.Relative position modification of SVM’s optimal hyperplane [J].Journal of Beijing University of Aeronautics and Astronautics,2009,35(11):1302-1305(in Chinese)
[4]
Fung G,Mangasarian O L.Proximal support vector machine classifiers [C]// Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York:ACM,2001:77-86
[5]
刘芸,唐发根,林广艳.一种改进的近似支持向量机算法[J].北京航空航天大学学报,2007,33(9):1090-1093 Liu Yun,Tang Fagen,Lin Guangyan.Robust proximal support vector machine [J].Journal of Beijing University of Aeronautics and Astronautics,2007,33(9):1090-1093(in Chinese)
[6]
Hao Peiyi.New support vector algorithms with parametric insensitive/margin model [J].Neural Networks,2010,23(1):60-73
[7]
Yeom H G,Jang I H,Sim K B.Variance considered machines:modification of optimal hyperplanes in support vector machines [C]// IEEE International Symposium on Industrial Electronics.Seoul:IEEE,2009:1144-1147
[8]
Vapnik V N.Statistical learning theory [M].New York:Wiley,1998
[9]
Yang Chanyun,Yang J Y,Wang Jianjun.Margin calibration in SVM class-imbalanced learning [J].Neurocomputing,2009,73 (13):397-411