| 最小二乘双支持向量机的在线学习算法 |
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| 引用本文： | 穆晓霞,陈留院,李钧涛.最小二乘双支持向量机的在线学习算法[J].计算机仿真,2012,29(3):25-28. |
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| 作者姓名： | 穆晓霞 陈留院 李钧涛 |
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| 作者单位： | 1. 河南师范大学计算机与信息技术学院,河南新乡,453007
2. 河南师范大学数学与信息科学学院,河南新乡,453007 |
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| 基金项目： | 河南省教育厅自然科学研究计划项目(2011B120005);河南师范大学青年科学基金(2010qk01,2010qk21) |
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| 摘 要： | 针对具有两个非并行分类超平面的最小二乘双支持向量机,提出了一种在线学习算法。通过利用矩阵求逆分解引理,所提在线学习算法能充分利用历史的训练结果,避免了大型矩阵的求逆计算过程,从而降低了计算的复杂性。仿真结果验证了所提学习算法的有效性。
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| 关 键 词： | 支持向量机 双支持向量机 最小二乘双支持向量机 在线学习 |
Online Learning Algorithm for Least Squares Twin Support Vector Machines |
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| MU Xiao-xia
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CHEN Liu-yuan
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LI Jun-tao.Online Learning Algorithm for Least Squares Twin Support Vector Machines[J].Computer Simulation,2012,29(3):25-28. |
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| Authors: | MU Xiao-xia CHEN Liu-yuan LI Jun-tao |
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| Affiliation: | 1.College of Computer & Information Technology,Henan Normal University,Xinxiang 453007,China; 2.College of Mathematics and Information Science,Henan Normal University,Xinxiang 453007,China) |
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| Abstract: | An online learning algorithm was proposed for solving the problem in designing least square twin support vector machines which have two nonparallel planes.By using the lemma of the inverse matrix decomposition,the proposed algorithm can fully utilize the historical training results and avoid the process of calculating the inverse matrix of large matrix,thus reducing the computational complexity.The simulation results demonstrate the effectiveness of the proposed algorithm. |
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| Keywords: | Support vector machines Twin support vector machines Least squares twin support vector machines Online learning |
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