Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support

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

Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan and Gilbert Chu
Statistical Science
Vol. 18, No. 1 (Feb., 2003), pp. 104-117
Stable URL: http://www.jstor.org/stable/3182873
Page Count: 14
  • Read Online (Free)
  • Subscribe ($19.50)
  • Cite this Item
If you need an accessible version of this item please contact JSTOR User Support
Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays
Preview not available

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 other high-dimensional classification problems. The method is illustrated on data from two gene expression studies: lymphoma and cancer cell lines.

Page Thumbnails

  • Thumbnail: Page 
104
    104
  • Thumbnail: Page 
105
    105
  • Thumbnail: Page 
106
    106
  • Thumbnail: Page 
107
    107
  • Thumbnail: Page 
108
    108
  • Thumbnail: Page 
109
    109
  • Thumbnail: Page 
110
    110
  • Thumbnail: Page 
111
    111
  • Thumbnail: Page 
112
    112
  • Thumbnail: Page 
113
    113
  • Thumbnail: Page 
114
    114
  • Thumbnail: Page 
115
    115
  • Thumbnail: Page 
116
    116
  • Thumbnail: Page 
117
    117