[1] Cortes C, Vapnik V N. Support-vector networks[J]. Machine Learning, 1995, 20(3):273-297.
[2] Vapnik V N. The nature of statistical learning theory[J]. Technometrics, 1997, 38(4):409.
[3] 丁晓剑, 赵银亮. 双边界支持向量机的理论研究与分析[J]. 北京邮电大学学报, 2010, 33(2):20-23. Ding Xiaojian, Zhao Yinliang. Theory and analysis of double margin SVM[J]. Journal of Beijing University of Posts and Telecommunications, 2010, 33(2):20-23.
[4] 马跃峰, 梁循, 周小平. 一种基于全局代表点的快速最小二乘支持向量机稀疏化算法[J]. 自动化学报, 2017, 43(1):132-141. Ma Yuefeng, Liang Xun, Zhou Xiaoping. A fast sparse algorithm for least squares support vector machine based on global representative points[J]. Acta Automatica Sinica, 2017, 43(1):132-141.
[5] 陈素根, 吴小俊. 改进的投影孪生支持向量机[J]. 电子学报, 2017, 45(2):408-416. Chen Sugen, Wu Xiaojun. Improved projection twin support vector machine[J]. Acta Electronica Sinica, 2017, 45(2):408-416.
[6] 刘春红, 韩晶晶, 商彦磊, 等. 基于SVM分类的云集群失败作业主动预测方法[J]. 北京邮电大学学报, 2016, 39(5):104-109. Liu Chunhong, Han Jingjing, Shang Yanlei, et al. Predicting job failure in cloud cluster:based on SVM classification[J]. Journal of Beijing University of Posts and Telecommunications, 2016, 39(5):104-109.
[7] Qi Zhiquan, Tian Yingjie, Shi Yong. Robust twin support vector machine for pattern classification[J]. Pattern Recognition, 2013, 46(1):305-316.
[8] Shao Yuanhai, Deng Naiyang, Yang Zhimin. Least squares recursive projection twin support vector machine for classification[J]. Pattern Recognition, 2012, 45(6):2299-2307.
[9] Chen Sugen, Wu Xiaojun. A new fuzzy twin support vector machine for pattern classification[J]. International Journal of Machine Learning and Cybernetics, 2018, 9(9):1553-1564.
[10] Tanveer M, Khan M A, Ho S S. Robust energy-based least squares twin support vector machines[J]. Applied Intelligence, 2016, 45(1):174-186.
[11] Mangasarian O L, Wild E W. Multisurface proximal support vector machine classification via generalized eigenvalues[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(1):69-74.
[12] Jayadeva, Khemchandani R, Chandra S. Twin support vector machines for pattern classification[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(5):905-910.
[13] Kumar M A, Gopal M. Least squares twin support vector machines for pattern classification[J]. Expert Systems with Applications, 2009, 36(4):7535-7543.
[14] Shao Yuanhai, Zhang Chunhua, Wang Xiaobo, et al. Improvements on twin support vector machines[J]. IEEE Transactions on Neural Networks, 2011, 22(6):962-968.
[15] 程昊翔, 王坚. 一种新的孪生大间隔分布机算法[J]. 控制与决策, 2016, 31(5):949-952. Cheng Haoxiang, Wang Jian. A novel twin large margin distribution machine[J]. Control and Decision, 2016, 31(5):949-952.
[16] Vapnik V N. Statistical learning theory[J]. Encyclopedia of the sciences of learning, 1998, 41(4):3185.
[17] Blake C. UCI repository of machine learning databases[EB/OL].[2017-06-25]. http://www.ics.uci.edu/~mlearn/MLRepository.html. |