DocumentCode :
1863468
Title :
Hybrid feature selection method using gene expression data
Author :
Chuang, Li-Yeh ; Wu, Kuo-Chuan ; Yang, Cheng-Hong
Author_Institution :
Dept. of Chem. Eng., I-Shou Univ., Kaohsiung
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
199
Lastpage :
204
Abstract :
Gene expression profiles, which represent the state of a cell at a molecular level, have great potential as a medical diagnosis tool. Compared to the number of genes involved available training data sets generally have a fairly small sample size in cancer type classification. These training data limitations constitute a challenge to certain classification methodologies. The gene (feature) selection can extract genes which influence classification accuracy effectively, to eliminate the useless genes, and to improve the calculate performance and the classification accuracy. This paper presents hybrid feature selection method - Taguchi-Genetic algorithm to find optimal feature subset, to appraise feature set using K-nearest neighbor with leave-one-out cross-validation based on Euclidean distance calculation. Experimental results show that our method simplifies features effectively and obtains a higher classification accuracy compared to other classification methods from the literature.
Keywords :
Taguchi methods; biology computing; feature extraction; genetic algorithms; genetics; pattern classification; Euclidean distance; K-nearest neighbor; Taguchi-genetic algorithm; classification accuracy; gene expression data; hybrid feature selection method; molecular level; optimal feature subset; Appraisal; Biomedical engineering; Cancer; DNA; Euclidean distance; Gene expression; Medical diagnosis; Production; Proteins; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing in Industrial Applications, 2008. SMCia '08. IEEE Conference on
Conference_Location :
Muroran
Print_ISBN :
978-1-4244-3782-5
Electronic_ISBN :
978-4-9904-2590-6
Type :
conf
DOI :
10.1109/SMCIA.2008.5045960
Filename :
5045960
Link To Document :
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