Close category search window
 

Ensemble determination using the TOPSIS decision support system in multi-objective evolutionary neural network classifiers

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

7 Author(s)
Cruz-Ramirez, M. ; Dept. of Comput. Sci. & Numerical Anal., Univ. of Cordoba, Cordoba, Spain ; Fernandez, J.C. ; Sanchez-Monedero, J. ; Fernandez-Navarro, F.
more authors

The selection of a particular neural network model belonging to the Pareto front is a problem that exists in all multi-objective algorithms. This paper proposes a novel solution to this problem based on a linear combination of the outputs of the two extremes in the Pareto front, which form an ensemble. The decision support TOPSIS method is used to determine which linear combination creates the best ensemble. This analysis selects the most representative individual that performs better in generalization than the extremes of the Pareto front do.

Published in:
Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on

Date of Conference: Nov. 29 2010-Dec. 1 2010

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 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.