By Topic

Evaluation Method and Application Based on Rough Set-Support Vector Regression 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

3 Author(s)
Xiu-Mei Wang ; Sch. of Bus. & Adm., North China Electr. power Univ., Baoding ; Xing Zhang ; Chong Gao

Support Vector Machine has the convenient superiority in the classification. Recently it has been extended to the domain of regression problems. However, due to the increasing index, excess input data and complicated system structure, it is difficult to achieve good accuracy in results. This paper adopts combination method of rough set and support vector machine so as to establish rough set attribute reducing support vector regression model to carry out the comprehensive evaluation of the innovative talents training in engineering universities. The experimental results show that this method has strong objectivity and impartiality, and can increase the computing speed.

Published in:

Computer Engineering and Technology, 2009. ICCET '09. International Conference on  (Volume:2 )

Date of Conference:

22-24 Jan. 2009