DocumentCode
3661108
Title
Multiple SVM-RFE for multi-class gene selection on DNA Microarray data
Author
Li Zhang; Xiaojuan Huang
Author_Institution
School of Computer Science and Technology &
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
1
Lastpage
6
Abstract
This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as multiple binary classification problems. First, the one-versus-all method is used to decompose the multi-class task into multiple binary problems. Second, an SVM-RFE is adopted to select genes for each binary problem. Then, an SVM classifier is used to train the selected gene data for a binary problem. Finally, we combine the outputs of multiple SVM classifiers. Experimental results on three DNA Microarray datasets show that the proposed method achieves higher classification accuracy.
Keywords
"DNA","Lungs","Bioinformatics"
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2015 International Joint Conference on
Electronic_ISBN
2161-4407
Type
conf
DOI
10.1109/IJCNN.2015.7280417
Filename
7280417
Link To Document