DocumentCode
2415009
Title
Speed up SVM-RFE Procedure Using Margin Distribution
Author
Yuan, Yingqin ; Hrebien, Leonid ; Kam, Moshe
Author_Institution
Res. & Eng. Center, Whirlpool Corp., Benton Harbor, MI
fYear
2005
fDate
28-28 Sept. 2005
Firstpage
297
Lastpage
302
Abstract
In this paper, a new method is introduced to speed up the recursive feature ranking procedure by using the margin distribution of a trained SVM. The method, M-RFE, continuously eliminates features without retraining the SVM as long as the margin distribution of the SVM does not change significantly. Synthetic datasets and two benchmark microarray datasets were tested on M-RFE. Comparison with original SVM-RFE shows that our method speeds up the feature ranking procedure considerably with little or no performance degradation. Comparison of M-RFE to a similar speed up technique, E-RFE, provides similar classification performance, but with reduced complexity
Keywords
feature extraction; pattern classification; support vector machines; SVM-recursive feature elimination; margin distribution; microarray dataset; pattern classification; recursive feature ranking; support vector machines; Acceleration; Accuracy; Benchmark testing; Cancer; Data engineering; Degradation; Entropy; Laboratories; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning for Signal Processing, 2005 IEEE Workshop on
Conference_Location
Mystic, CT
Print_ISBN
0-7803-9517-4
Type
conf
DOI
10.1109/MLSP.2005.1532917
Filename
1532917
Link To Document