Improved Centroids Estimation for the Nearest Shrunken Centroid ClassifierAuthors: Sijian Wang and Ji Zhu*
The nearest shrunken centroid (NSC) method has been successfully applied in many DNA microarray classification problems. We show that the NSC method can be interpreted in the framework of LASSO regression. Based on that, we consider two new methods for microarray classification, which improve over the NSC. Unlike the L1-norm penalty used in LASSO, the penalty terms that we consider make use of the fact that parameters belonging to one gene should be treated as a natural group. Numerical results indicate that the two new methods tend to remove irrelevant genes more effectively and provide better classification results than the L1-norm approach.