Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays
Statistical SciencePublished 1 February 2003Open access
Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, Gilbert Chu
Citations425
SJR quartileQ1
SJR score1.67
SNIP2.24
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TL;DR
This work proposes a new method for class prediction in DNA microarray studies based on an enhancement of the nearest prototype classifier that uses "shrunken" centroids as prototypes for each class to identify the subsets of the genes that best characterize each class.
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.
Keywords
Biochemistry, Genetics and Molecular Biology
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