| 大数据分析过程中的降维方法 |
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| 引用本文： | 郝晓军,闫京海,樊友谊.大数据分析过程中的降维方法[J].航天电子对抗,2014(4):58-60. |
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| 作者姓名： | 郝晓军 闫京海 樊友谊 |
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| 作者单位： | 电子信息系统复杂电磁环境效应国家重点实验室,河南洛阳471003 |
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| 摘 要： | 随着大数据时代的到来,高维数组的分析越来越困难。介绍了两种大数据线性降维的方法,通过构造计算矩阵,求解矩阵的特征值和特征向量,可以非常容易地发现数据的极小维度表示,降低后期大数据分析的复杂度。通过采用这些方法进行数据降维,可以找出数据内在的相互关系,非常有利于数据分布规律的分析。
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| 关 键 词： | 降维 主分量分析 多维尺度分析 |
Dimensionality reduction of large volumes of data analysis |
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| Hao Xiaojun,Yan Jinghai,Fan Youyi.Dimensionality reduction of large volumes of data analysis[J].Aerospace Electronic Warfare,2014(4):58-60. |
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| Authors: | Hao Xiaojun Yan Jinghai Fan Youyi |
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| Institution: | (State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang 471003, Henan, China) |
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| Abstract: | With the large volume of data coming,high dimensional data is very difficult to be analyzed.The two ways are introduced to reduce the dimensionality of large volumes of data.These methods are able to reveal low dimensional structure of high dimensional data from the top or bottom eigenvectors of specially constructed matrices,and can reduce the complexity of data analysis.Based on these ways,the intrinsic connection between the data can be got easily,and which is helpful to research the distributing rules. |
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| Keywords: | dimensionality reduction principal component analysis metric multidimensional scaling |
| 本文献已被 CNKI 维普 等数据库收录！ |
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