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BMCBI
2006

Gene selection algorithms for microarray data based on least squares support vector machine

8 years 10 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary to conduct the discriminant analysis with all the genes. Hence, gene selection is usually performed to select important genes. Results: A gene selection method searches for an optimal or near optimal subset of genes with respect to a given evaluation criterion. In this paper, we propose a new evaluation criterion, named the leave-one-out calculation (LOOC, A list of abbreviations appears just above the list of references) measure. A gene selection method, named leave-one-out calculation sequential forward selection (LOOCSFS) algorithm, is then presented by combining the LOOC measure with the sequential forward selection scheme. Further, a novel gene selection algorithm, the gradientbased leave-one-out gene selection (GLGS) algorithm, is also proposed. Both of the gene selection algorithms originate from an ef...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2006
Where BMCBI
Authors E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
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