Abstract
In order to filter noisy and redundant genes, this paper presents a two-step gene feature selection algorithm based on permutation Test. The proposed algorithm can select genes efficiently and process large dataset quickly due to the permutation test technique. Twelve datasets of RSCTC 2010 Discovery Challenge and two famous classifiers SVM and PAM are adopted to evaluate the performance of the proposed algorithm. The experiment results show that the small gene subset with high discriminant and low redundancy can be selected efficiently by the proposed algorithm.
Part of this work is supported by National Natural Science Foundation of China (No. 61073146), Cooperation Project between China and Poland in Science and Technology ([2010]179)
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References
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Luo, C., Wang, G., Hu, F. (2012). Two-Step Gene Feature Selection Algorithm Based on Permutation Test. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_30
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DOI: https://doi.org/10.1007/978-3-642-32115-3_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32114-6
Online ISBN: 978-3-642-32115-3
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