Exploiting the accumulated evidence for gene selection in microarray gene expression data
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Feature subset selection (FSS) methods play an important role for cancer classification using microarray gene expression data. In this scenario, it is extremely important to select genes by taking into account the possible interactions with other gene subsets. This paper shows that, by accumulating the evidence in favour (or against) each gene along a search process, the obtained gene subsets may constitute better solutions, either in terms of size or in predictive accuracy, or in both, at a negligible overhead in computational cost.
CitationPrat, G.; Belanche, Ll. Exploiting the accumulated evidence for gene selection in microarray gene expression data. A: European Conference on Artificial Intelligence. "ECAI 2010, 19th European Conference on Artificial Intelligence: 16-20 August 2010, Lisbon, Portugal: Including Prestigious Applications of Artificial Intelligence (PAIS-2010): proceedings". Lisboa: IOS Press, 2010, p. 989-990.