| 基于内核的低秩逼近算法的改进 |
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| 引用本文： | 高超.基于内核的低秩逼近算法的改进[J].哈尔滨商业大学学报(自然科学版),2013(6):691-693. |
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| 作者姓名： | 高超 |
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| 作者单位： | 哈尔滨工程大学信息与通信工程学院,哈尔滨150001 |
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| 摘 要： | 为进一步提高低秩逼近技术的逼近精度,提出了一种改进的基于内核的低秩逼近算法（IK-BLA）.算法利用在数值上呈现递减规律的、与矩阵列相关的非均匀概率分布函数对大规模n×n矩阵W进行抽样,接着用抽样得到的小规模c×c矩阵W逼近矩阵W.在UCI数据库中部分数据集上的实验验证了IKBLA的有效性.
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| 关 键 词： | 低秩逼近技术 逼近精度 递减规律 非均匀概率分布 |
Improved kernel-based algorithm using low-rank approximation |
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| GAO Chao.Improved kernel-based algorithm using low-rank approximation[J].Journal of Harbin University of Commerce :Natural Sciences Edition,2013(6):691-693. |
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| Authors: | GAO Chao |
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| Institution: | GAO Chao (School of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China) |
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| Abstract: | In order to further improve the approximation accuracy of low rank approximation technique, an improved kernel-based algorithm using low-rank approximation method （IK- BLA） was proposed in this paper. IKBLA used a matrix columns-dependent non-uniform probability distribution with values subjecting to the law of diminishing to sample the large scale n x n matrix W. Next, approach the matrix W with small scale c x c matrix 17V. Experi- ments in some datasets in UCI database showed the effectiveness of IKBLA. |
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| Keywords: | low-rank approximation method approximation accuracy law of diminishing non-uniform probability distribution |
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