By Topic

Fuzzy data domain description using support vector machines

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Li-Li Wei ; Inst. of Inf. & Syst. Sci., Xi''an Jiaotong Univ., China ; Wei-Jiang Long ; Wen-Xiu Zhang

In this paper, we reformulate the use of a data domain description method, inspired by the fuzzy support vector machine (SVM) by Lin, called the fuzzy data domain description. This data description is suitable for applications in which each input point may not be fully assigned to one class. In this method, different input data can make different contributions to the domain description.

Published in:

Machine Learning and Cybernetics, 2003 International Conference on  (Volume:5 )

Date of Conference:

2-5 Nov. 2003