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 :
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