Title :
A feature selection method based on minimizing generalization bounds of SVM via GA
Author :
Xu, J.Q. ; Yuan, Z.D.
Author_Institution :
Center of Math. & Phys. Teaching, Shanghai Inst. of Technol., China
Abstract :
A method based on finding those features which minimizing a kind of generalization bounds of the SVM is presented. The searching can be efficiently implemented via genetic algorithm. The resulting algorithm is shown to be effective on both simulation datasets and the real cardiac pattern recognition.
Keywords :
cardiology; feature extraction; genetic algorithms; support vector machines; GA; SVM; feature selection method; generalization bounds; genetic algorithm; minimization; real cardiac pattern recognition; simulation datasets; support vector machines;
Conference_Titel :
Intelligent Control. 2003 IEEE International Symposium on
Conference_Location :
Houston, TX, USA
Print_ISBN :
0-7803-7891-1
DOI :
10.1109/ISIC.2003.1254773
