DocumentCode
3339386
Title
A Novel Evaluation Method Basing on Support Vector Machines
Author
Xian, Guang-Ming ; Zeng, Bi-qing
Author_Institution
Dept. of Comput. Eng., South China Normal Univ., Foshan
fYear
2008
fDate
24-26 April 2008
Firstpage
316
Lastpage
319
Abstract
Recently support vector machine (SVM) has become a more and more popular classification tool. We presented our two-phase, efficient, and fair evaluation method for DRMs (digital right management system) basing on SVM. Influence of three difference methods and test set number on evaluation result is discussed. After analysized by binary logistic regression, odds ratio comparison of SVM with multi-phase fuzzy synthesized evaluation and FCM illustrates that SVM is the most excellent in these three approaches. Through detailed experimental evaluations under various data set of samples and approaches, our evaluation method of SVM is illustrated to be scalable and accurate.
Keywords
fuzzy set theory; regression analysis; support vector machines; binary logistic regression; digital right management system; fuzzy c-mean; multiphase fuzzy synthesized evaluation; support vector machines; Clustering algorithms; Graphics; Iterative algorithms; Logistics; Machine learning; Pervasive computing; Support vector machine classification; Support vector machines; Testing; Web services; FCM; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Ubiquitous Engineering, 2008. MUE 2008. International Conference on
Conference_Location
Busan
Print_ISBN
978-0-7695-3134-2
Type
conf
DOI
10.1109/MUE.2008.111
Filename
4505742
Link To Document