Distributed feature selection: An application to microarray data classification
Feature selection is indispensable when dealing with microarray data. A new method for distributing the filtering process is proposed. The data is distributed by features and then merged in a final subset. The method is tested on 8 microarray datasets. The classification accuracy is maintained and the time considerably shortened.
feature selection microarray data distributed learning