Class prediction by nearest shrunken centroids, with applications to DNA microarrays

被引：274

作者：

Tibshirani, R ^{[1
]}

Hastie, T

Narasimhan, B

Chu, G

机构：

[1] Stanford Univ, Dept Hlth Res & Policy, Stanford, CA 94305 USA

[2] Stanford Univ, Dept Stat, Stanford, CA 94305 USA

[3] Stanford Univ, Dept Biochem, Stanford, CA 94305 USA

[4] Stanford Univ, Dept Med Oncol, Stanford, CA 94305 USA

来源：

STATISTICAL SCIENCE | 2003年 / 18卷 / 01期

关键词：

sample classification; gene expression arrays;

D O I：

10.1214/ss/1056397488

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We propose anew method for class prediction in DNA microarray studies based on an enhancement of the nearest prototype classifier. Our technique uses "shrunken" centroids as prototypes for each class to identify the subsets of the genes that best characterize each class. The method is general and can be applied to other high-dimensional classification problems. The method is illustrated on data from two gene expression studies: lymphoma and cancer cell lines.

引用

页码：104 / 117

页数：14

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