Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/114981
Title: A new method on gene selection for tissue classification
Authors: Hao, Y.
Meng, F. 
Keywords: Classification
Fisher's linear discriminant
Gene selection
Support vector machines
Issue Date: 2007
Citation: Hao, Y.,Meng, F. (2007). A new method on gene selection for tissue classification. Journal of Industrial and Management Optimization 3 (4) : 739-748. ScholarBank@NUS Repository.
Abstract: Tumor classification is one of the important applications of microarray technology. In gene expression-based tumor classification systems, gene selection is a main and very important component. In this paper, we propose a new approach for gene selection. With the genes selected in colon cancer data, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) data using our approach, we apply support vector machines to classify tissues in these two data sets, respectively. The results of classification show that our method is very useful and promising.
Source Title: Journal of Industrial and Management Optimization
URI: http://scholarbank.nus.edu.sg/handle/10635/114981
ISSN: 15475816
Appears in Collections:Staff Publications

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