| 高维数据降维算法综述 |
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| 引用本文： | 景明利.高维数据降维算法综述[J].西安文理学院学报,2014(4):48-52. |
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| 作者姓名： | 景明利 |
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| 作者单位： | 西安财经学院统计学院; |
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| 基金项目： | 陕西省统计研究中心资助项目(13JD03) |
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| 摘 要： | 分类介绍了目前具有代表性的数据降维方法,重点阐述了一种新的数据降维方法 -压缩感知,在此基础上,分析了各种数据降维算法的优缺点,并对数据降维研究中存在的问题进行了剖析.
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| 关 键 词： | 数据降维 线性 非线性 局部 压缩感知 |
A Summary of Dimension Reduction for High Dimensional Data |
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| JING Ming-li.A Summary of Dimension Reduction for High Dimensional Data[J].Journal of Xi‘an University of Arts & Science:Natural Science Edition,2014(4):48-52. |
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| Authors: | JING Ming-li |
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| Institution: | JING Ming-li (School of Statistics, Xi＇an University of Finance and Economics, Xi＇an 710100 ,China) |
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| Abstract: | This paper classifies the current representative data dimension reductions and elabo- rates on compressed sensing, a new dimension reduction method. The advantages and disad- vantages of the various data dimension reductions are analyzed. A summary of the problematic issues in the research field is also given. |
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| Keywords: | data dimension reduction linearity nonlinearity partiality compression |
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