By Topic

A fuzzy support vector machine based on geometric model

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

2 Author(s)
Leilei Chu ; Fac. of Sci., Xi''an Jiaotong Univ., China ; Chengdong Wu

Fuzzy support vector machine is a learning algorithm used to solve the classification problems based on statistical learning theory and fuzzy properties of training points. To determine the fuzzy membership of the training points, the guard vector method and the circle method are proposed using the fuzzy membership function and the geometrical properties of the distribution of the training points in space. Numerical experiments indicate that the two methods improve the accuracy of classification and takes a shorter training time.

Published in:

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on  (Volume:2 )

Date of Conference:

15-19 June 2004