2007 Frontiers in the Convergence of Bioscience and Information Technologies Selecting Informative Genes from Microarray Data for Cancer Classification with Genetic Programming Classifier Using K-Means Clustering and SNR Ranking Jeju Island, Korea October 11-October 13 ISBN: 978-0-7695-2999-8
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FBIT.2007.84
This paper presents a method for selecting informative features using K-Means clustering and SNR ranking. The performance of the proposed method was tested on cancer classification problems. Genetic Programming is employed as a classifier. The experimental results indicate that the proposed method yields higher accuracy than using the SNR ranking alone and higher than using all of the genes in classification. The clustering step assures that the selected genes have low redundancy, hence the classifier can exploit these features to obtain better performance.
Citation:
Supoj Hengpraprohm, Prabhas Chongstitvatana, "Selecting Informative Genes from Microarray Data for Cancer Classification with Genetic Programming Classifier Using K-Means Clustering and SNR Ranking," fbit, pp.211-218, 2007 Frontiers in the Convergence of Bioscience and Information Technologies, 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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