Cart (Loading....) | Create Account
Close category search window

Student Survey by Information-Theoretic Competitive Learning

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

1 Author(s)
Kamimura, R. ; Tokai Univ., Kanagawa

In this paper, we apply our information-theoretic method to a student survey. The information-theoretic method aims to extract main features in input patterns by condensing information contained in input patterns as much as possible. By using 2500 students' responses to the questionnaire, we could extract the main subjects in which the majority of students have interest. Especially, we could classify students into several groups by their interest. On the other hand, the conventional PCA could not demonstrate specific features in input patters. Thus, the information-theoretic neural methods can open up a new perspective for data analyses.

Published in:

Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on  (Volume:6 )

Date of Conference:

8-11 Oct. 2006

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.