Statistical Science
- Statist. Sci.
- Volume 18, Issue 1 (2003), 104-117.
Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays
Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, and Gilbert Chu
Abstract
We propose a new 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 the other high-dimensional classification problems. The method is illustrated on data from two gene expression studies: lymphoma and cancer cell lines.
Article information
Source
Statist. Sci. Volume 18, Issue 1 (2003), 104-117.
Dates
First available in Project Euclid: 23 June 2003
Permanent link to this document
http://projecteuclid.org/euclid.ss/1056397488
Digital Object Identifier
doi:10.1214/ss/1056397488
Mathematical Reviews number (MathSciNet)
MR1997067
Zentralblatt MATH identifier
1048.62109
Keywords
Sample classification gene expression arrays.
Citation
Tibshirani, Robert; Hastie, Trevor; Narasimhan, Balasubramanian; Chu, Gilbert. Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays. Statist. Sci. 18 (2003), no. 1, 104--117. doi:10.1214/ss/1056397488. http://projecteuclid.org/euclid.ss/1056397488.

