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Due to the advantage of achieving a better performance under weakregularization, elastic net has attracted wide attention in statistics, machinelearning, bioinformatics, and other fields. In particular, a variation of theelastic net, adaptive elastic net (AEN), integrates the adaptive groupingeffect. In this paper, we aim to develop a new algorithm: Adaptive Elastic Netwith Conditional Mutual Information (AEN-CMI) that further improves AEN byincorporating conditional mutual information into the gene selection process.We apply this new algorithm to screen significant genes for two kinds ofcancers: colon cancer and leukemia. Compared with other algorithms includingSupport Vector Machine, Classic Elastic Net and Adaptive Elastic Net, theproposed algorithm, AEN-CMI, obtains the best classification performance usingthe least number of genes.

Informative Gene Selection for Microarray Classification via Adaptive Elastic Net with Conditional Mutual Information