Exploiting the Accumulated Evidence for Gene Selection in Microarray Gene Expression Data
作者： Lluís A. Belanche-Muòoz , Gabriel Prat-Masramon
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摘要: Feature subset selection (FSS) methods play an important role for cancer classification using microarray gene expression data. In this scenario, it is extremely to select genes by taking into account the possible interactions with other subsets. This paper shows that, accumulating evidence in favour (or against) each along a search process, obtained subsets may constitute better solutions, either terms of size or predictive accuracy, both, at negligible overhead computational cost.
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