You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays
Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan and Gilbert Chu
Vol. 18, No. 1 (Feb., 2003), pp. 104-117
Published by: Institute of Mathematical Statistics
Stable URL: http://www.jstor.org/stable/3182873
Page Count: 14
You can always find the topics here!Topics: Centroids, Error rates, Linear discriminant analysis, Simulations, Standard deviation, Covariance, Zero, Lymphoma, Discriminant analysis, Genes
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
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 other high-dimensional classification problems. The method is illustrated on data from two gene expression studies: lymphoma and cancer cell lines.
Statistical Science © 2003 Institute of Mathematical Statistics