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[1]周欣然,滕召胜,易钊,等.构造稀疏最小二乘支持向量机的快速剪枝算法[J].电机与控制学报,2009,(04):626-630.
 ZHOU Xin-ran,TENG Zhao-sheng,et al.Fast pruning algorithm for designing sparse least squares support vector machine[J].,2009,(04):626-630.
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构造稀疏最小二乘支持向量机的快速剪枝算法(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2009年04
页码:
626-630
栏目:
出版日期:
2009-07-15

文章信息/Info

Title:
Fast pruning algorithm for designing sparse least squares support vector machine
作者:
周欣然; 滕召胜; 易钊;
湖南大学电气与信息工程学院; 中南大学信息科学与工程学院;
Author(s):
ZHOU Xin-ran1; 2; TENG Zhao-sheng1; YI Zhao1
1.College of Electrical and Information Engineering; Hunan University; Changsha 410082; China; 2.School of Information Science and Engineering; Central South University; Changsha 410075; China
关键词:
最小二乘支持向量机 稀疏性 剪枝算法 置换矩阵 分块矩阵
Keywords:
least squares support vector machine sparsity pruning algorithm permutation matrix partitioned matrix
分类号:
TP18
DOI:
-
文献标志码:
A
摘要:
为了减少最小二乘支持向量机基本剪枝算法的计算量,提出一种快速剪枝算法。在分析剪枝前后两个最小二乘支持向量机对应线性方程组系数矩阵之间关系的基础上,利用置换矩阵的逆等于其转置的性质和分块矩阵求逆公式,导出两个系数矩阵的子阵的逆之间的递推关系,避免剪枝过程中多次进行高阶矩阵求逆,从而减少计算量。在不考虑计算误差时,该算法理论上得出与基本剪枝算法相同结果的稀疏最小二乘支持向量机。仿真结果表明该算法比基本剪枝算法速度快,而且初始训练样本越多,加速比越大。
Abstract:
To reduce the computation amount of basic pruning algorithm(BPA) for least squares support vector machine(LSSVM),a fast pruning algorithm(FPA) is proposed.The connection between two coefficient matrices of linear equations corresponding to LSSVM before pruning and to one after doing is analyzed,and the recursive relation between inversions of sub-matrices of the two coefficient matrices is derived by permutation matrix’s property of its inversion equalling to its transpose by the calculation formula of solv...

参考文献/References:

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备注/Memo

备注/Memo:
国家自然科学基金(60872128);; 技术创新基金项目(07C26214301740
更新日期/Last Update: 2010-05-25