Abstract
Gene selection is a significant preprocessing of the discriminant analysis of microarray data. The classical gene selection methods can be classified into three categories: the filters, the wrappers and the embedded methods. In this paper, a novel hybrid gene selection method (HGSM) is proposed by exploring both the mutual information criterion (filters) and leave-one-out-error criterion (wrappers) under the framework of an improved ant algorithm. Extensive experiments are conducted on three benchmark datasets and the results confirm the effectiveness and efficiency of HGSM.
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Acknowledgments
This work is partial supported by National Natural Science Foundation of China (60873078), Key Natural Science Foundation of Guangdong Province (9251009001000005, 9151600301000001), Key Technology Research and Development Programs of Guangdong Province (2008B080701005, 2009B010800026), Social Science Foundation of Guangdong Province (08O-01), Open Foundation of the State Key Laboratory of Information Security (04-01), Technology Research and Development Program of Huizhou (08-117), Doctoral Program of the Ministry of Education (20090172120035), and the Fundamental Research Funds for the Central Universities, SCUT(2009ZM0052).
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Cai, R., Hao, Z., Yang, X. et al. A new hybrid method for gene selection. Pattern Anal Applic 14, 1–8 (2011). https://doi.org/10.1007/s10044-010-0180-z
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DOI: https://doi.org/10.1007/s10044-010-0180-z