CAJ | 학술논문

为了对高维的基因表达数据进行有效的降维,本研究采用基于Fisher准则的思想对特征空间进行特征组合,从而得到新的特征空间。实验结果表明,在无法对数据再进行降维的原特征空间中,经过线性变换的方法得到的新特征空间可继续对其数据进行降维。通过这种方法,能将四川省医学科学院动物研究所所提供的抑郁症大鼠DNA的基因表达数据有效地从4353维降到1393维。
위료대고유적기인표체수거진행유효적강유,본연구채용기우Fisher준칙적사상대특정공간진행특정조합,종이득도신적특정공간。실험결과표명,재무법대수거재진행강유적원특정공간중,경과선성변환적방법득도적신특정공간가계속대기수거진행강유。통과저충방법,능장사천성의학과학원동물연구소소제공적억욱증대서DNA적기인표체수거유효지종4353유강도1393유。
In order to get effective dimension reduction in high-dimensional gene expression data,this paper is to introduce the experiment of re-combining the original feature space to get the new feature dimension by applying Fisher principle.The results show that,through the linear transformation,the new feature dimension can continue to reduce the dimension of its data,which can not be reduced in the original one.In this way,the date of rats＇ DNA gene expression data provided by Sichuan Academy of Medical Sciences and Institute of Zoology can be reduced from 4353 dimension to 1393 dimension effectively.