Statistical Science

Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays

Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, and Gilbert Chu

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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: 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
02068942

Citation

Tibshirani, Robert; Hastie, Trevor; Narasimhan, Balasubramanian; Chu, Gilbert. Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays. Statistical Science 18 (2003), no. 1, 104--117. doi:10.1214/ss/1056397488. http://projecteuclid.org/euclid.ss/1056397488.


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References

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