Class prediction by nearest shrunken centroids, with applications to DNA microarrays

We propose anew 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.