| 引用本文: | 胡庆军,吴翊.Cρ 准则下选择最优子集的并行算法.[J].国防科技大学学报,1993,15(2):94-98.[点击复制] |
| Hu Qingjun,Wu Yi.A Parallel Algorithm of Selecting the Best Subset on Cρ Criterion[J].Journal of National University of Defense Technology,1993,15(2):94-98[点击复制] |
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| Cρ 准则下选择最优子集的并行算法 |
| 胡庆军, 吴翊 |
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(系统工程与应用数学系)
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| 摘要: |
| Cρ 准则[1]是目前颇受重视的一种变量选择准则。本文针对大型线性回归模型，推导了从所有可能子集中用Cρ准则选择最优子集的(乘除法)运算次数，提出了Cρ准则下变量选择的并行算法。给出了在 YH-l和 YH-2 向量巨型计算机上运行该算法的模拟结果且获得了15 倍左右的向量加速比s/v，体现了该算法的优越性。 |
| 关键词: 线性回归模型，变量选择准则，子集回归，并行计算，向量加速比 |
| DOI： |
| 投稿日期：1991-07-16 |
| 基金项目: |
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| A Parallel Algorithm of Selecting the Best Subset on Cρ Criterion |
| Hu Qingjun, Wu Yi |
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(Department of System Engineering and Applied Mathematics)
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| Abstract: |
| The Cρ criterion[l] is recently paid much attention to as an important one of variable selection. A parallel algorithm and the number of operations (multiplications and divisions) of selecting the best subset from a11 possible subsets，with regard to a large-scale linear regression model under Cρ criterion，are presented. The simulation results for the algorithm on the vector super-computers YH-1 and YH-2 are given. The vector speed-up，ratio，s/v, approximates to fifteen and the advantages of the algorithm are shown. |
| Keywords: linear regression model,variable selection criterion,subset regression,parallel computation,vector speed-up ratio |
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