DocumentCode
1562926
Title
Performance analysis and comparison of neural networks and support vector machines classifier
Author
Zheng, Enhui ; Li, Ping ; Song, Zhihuan
Author_Institution
Inst. of Ind. Process Control, Zhejiang Univ., Hangzhou, China
Volume
5
fYear
2004
Firstpage
4232
Abstract
The theory foundation and classification algorithm of neural networks (NN) and support vector machines (SVM) are researched and compared from their conceptual constructs to basic mathematical reasons, on the basis of which the SVM classification system and the NN classification system are constructed respectively. The performances of the two classification systems are tested on two sets of benchmark data, and the SVM classification system shows better performance in binary classification tasks.
Keywords
learning (artificial intelligence); minimisation; neural nets; pattern classification; support vector machines; SVM classification system; binary classification tasks; classification algorithm; learning algorithm; mathematical reasons; minimization; neural network classification system; performance analysis; support vector machines; Least squares approximation; Neural networks; Pattern recognition; Performance analysis; Risk management; Statistical learning; Support vector machine classification; Support vector machines; System testing; Virtual colonoscopy;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1342308
Filename
1342308
Link To Document