HIGH DIMENSIONAL FEATURE SELECTION FOR DISCRIMINANT MICROARRAY DATA ANALYSIS

摘要

Gene selection is an important issue in microarray data analysis and has critical implications for the discovery of genes related to serious diseases. This paper proposes a Fisher optimization model in gene selection and uses Fisher linear discriminant in classification. Experiment result in public data has demonstrated validity of this method.