Indexed by：
Abstract：
© 2017 ICIC International.Compared with traditional support vector machine (SVM), twin support vector machine (TWSVM) has faster speed. The same penalties are given to the samples in TWSVM. In fact, samples in the different positions have different effects on the bound function. Then, dual fuzzy parameters are introduced and a fuzzy twin support vector machine based on the affinity of dual membership (DM-AFTWSVM) is presented. Numerical experiments on UCI datasets demonstrate the classification accuracy of twin support vector machine is improved.
Keyword：
Reprint Author's Address：
Email：
Source ：
ICIC Express Letters
ISSN： 1881-803X
Year： 2017
Issue： 2
Volume： 11
Page： 445-449
Cited Count：
WoS CC Cited Count： 0
SCOPUS Cited Count：
ESI Highly Cited Papers on the List： 0 Unfold All
WanFang Cited Count：
Chinese Cited Count：
30 Days PV： 9
Affiliated Colleges：
