LI Kai , HU Shaofang , WANG Liang , DONG Hua , XU Jianzhong . Fuzzy twin support vector machine based on iterative method[J]. Journal of Hebei University(Natural Science Edition), 2015 , 35(4) : 399 -404 . DOI: 10.3969/j.issn.1000-1565.2015.04.011

[1] 丁胜锋, DING Sheng-feng. 一种改进的双支持向量机 [J]. 辽宁石油化工大学学报 2012.doi:10.3696/j.issn.1672-6952.2012.04.020
[2] 丁胜锋, 孙劲光, DING Sheng-feng, SUN Jin-guang. 基于混合模糊隶属度的模糊双支持向量机研究 [J]. 计算机应用研究 2013.doi:10.3969/j.issn.1001-3695.2013.02.031
[3] LE T, TRAN D, MA W. Robust support vector machine [A]. 北京 2014.
[4] Bloom, V., Griva, I., Kwon, B., Wolff, A.. Exterior-Point Method for Support Vector Machines [J]. IEEE transactions on neural networks and learning systems 2014, 7(7).
[5] Jayadeva, R. Khemchandani, Suresh Chandra. Twin Support Vector Machines for Pattern Classification [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence 2007, 5(5).
[6] PENG Xinjun. A v-twin support vector machine(v-TSVM)classifier and its geometric algorithms [J]. Information Sciences 2010, 180.
[7] SHAO Yuanhai, ZHANG Chunhua, DENG Naiyang. Improvements on twin support vector machine [J]. IEEE Transactions on Neural Networks 2011, 22(06).
[8] Shifei Ding, Junzhao Yu, Bingjuan Qi, Huajuan Huang. An overview on twin support vector machines [J]. Artificial Intelligence Review: An International Science and Engineering Journal 2014, 2(2).
[9] Mangasarian Olvi L., Musicant David R.. Successive overrelaxation for support vector machines [J]. IEEE Transactions on Neural Networks 1999, 5(5).
[10] BLAKE C, MERZ C J. UCI Repository for machine learning databases [EB/OL]. IrvineCA:University of California, Department of Information and Computer Sciences 2014.