高等学校化学学报

高等学校化学学报 ›› 1998, Vol. 19 ›› Issue (7): 1054.

• 论文 • 上一篇    下一篇

人发微量元素与性别关系的模式识别分类研究

章元, 朱尔一, 庄峙厦, 李波, 王小如   

  1. 厦门大学化学系, 材料和生命过程分析科学国家教委开放研究实验室, 厦门, 361005
  • 收稿日期:1997-11-25 出版日期:1998-07-24 发布日期:1998-07-24
  • 通讯作者: 朱尔一
  • 作者简介:章元,男,24岁,硕士研究生.
  • 基金资助:

    国家教育委员会留学回国人员科研启动费及福建省自然科学基金资助课题.

Classification Study by Pattern Recognition on the Relationship Between the Trace Elements in Human Hair and Sex

ZHANG Yuan, ZHU Er-Yi, ZHUANG Zhi-Xia, LI Bo, WANG Xiao-Ru   

  1. Department of Chemistry, The SEDC Research Laboratory of Analytical Science for Material and Life Chemistry, Xiamen University, Xiamen, 361005
  • Received:1997-11-25 Online:1998-07-24 Published:1998-07-24

PDF (PC)

被引次数

15

摘要： 通过对人发样品中22种元素含量的数据进行变量扩维及压缩筛选处理,选出了影响性别判断较显著的变量,用PLS法处理这些变量组成的数据,得到男性与女性分类清晰的二维判别图及预报模型,并根据所建立的预报模型及人发微量元素的含量判别人的性别,准确率为81%.

关键词: 变量筛选, PLS回归, 微量元素

Abstract: The data of 22 trace elements concentrations in human hair samples were obtained by ICP-AES and GFAAS. The variables which have significant influence on discriminating the sex are selected through the treatment of the concentration data by the variable dimension expansion and the variable selection methods. The discrimination plane figure with the good classification is obtained through the treatment of the data with selected variables by PLSmethod. The prediction models are built and used to distinguish the human sex according to the element concentrations data in human hair. The accuracy of the prediction is 81%.

Key words: Model selection, PLS regression, Trace element

中图分类号: 

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