DocumentCode :
2370317
Title :
A cooperative feature gene extraction algorithm that combines classification and clustering
Author :
Chow, Chi Kin ; Zhu, Hailong ; Lacy, Jessica ; Lingen, Mark W. ; Kuo, Winston Patrick ; Chan, Keith
Author_Institution :
Hong Kong Polytech. Univ., Hung Hom, China
fYear :
2009
fDate :
1-4 Nov. 2009
Firstpage :
197
Lastpage :
202
Abstract :
In feature gene selection, filtering model concerns classification accuracy while ignoring gene redundancy problem. On the other hand, gene clustering finds correlated genes without considering their predictive abilities. It is valuable to enhance their performances by the help of each other. We report a new feature gene extraction algorithm, namely double-thresholding extraction of feature gene (DEFG), that combines gene filtering and gene clustering. It firstly pre-select feature gene set from the original dataset. A modified gene clustering is then applied to refine this set. In the gene clustering, specific designs are employed to balance the predictive abilities and the redundancies of the extracted feature gene. We have tested DEFG on a microarray dataset and compared its performance with that of two benchmark algorithms. The experimental results show that DEFG is superior to them in terms of internal validation accuracy and external validation accuracy. Also, DEFG can generalize the pattern structure by a small number of training samples.
Keywords :
biology computing; feature extraction; information filtering; pattern classification; pattern clustering; cooperative feature gene extraction algorithm; feature extraction algorithm; feature gene selection; filtering model; gene filtering; gene redundancy problem; microarray dataset; modified gene clustering; pattern structure; Classification algorithms; Clustering algorithms; Clustering methods; Data mining; Diseases; Feature extraction; Filtering algorithms; Performance evaluation; Support vector machines; Testing; Feature gene; classification; clustering; extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-5121-0
Type :
conf
DOI :
10.1109/BIBMW.2009.5332126
Filename :
5332126
Link To Document :
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