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一种针对区间型数据的新主成分分析法 被引量:3

A new principal component analysis method for interval data
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摘要 为了减少数据信息的损失,采用推迟区间型数据转换为数值型数据的方法,提出一种针对区间型数据的新的主成分分析方法.它和已有方法的区别在于协方差矩阵和相关矩阵的元素是区间数(从而相关的特征值和特征向量的元素也是区间数).最后用实例验证了该方法的优越性. To diminish loss of data,a new principal component analysis method for interval data is proposed by postpone the transformation from interval-type data to ordinary data.The method differs from existing methods in the location of factors(i.e.interval numbers)of the covariance matrix and the correlation matrix and thus their eigenvalues and eigenvectors.Examples are presented in the final part to illustrate the advantages of this method.
出处 《纺织高校基础科学学报》 CAS 2016年第2期184-189,共6页 Basic Sciences Journal of Textile Universities
基金 陕西省自然科学基金资助项目(2010JM1005) 陕西师范大学研究生教学改革与研究项目(GERP-14-04)
关键词 区间型数据 主成分分析方法 相关矩阵 interval data principal component analysis correlation matrix
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参考文献9

  • 1陈塑寰,邱志平,宋大同,陈宇东.区间矩阵标准特征值问题的一种解法[J].吉林工业大学学报,1993,23(3):1-8. 被引量:10
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二级参考文献15

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