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

A probabilistic approach for multi-objective clustering using game theory

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)
Badami, M. ; Sch. of Electr. & Comput. Eng., Shiraz Univ., Shiraz, Iran ; Hamzeh, A. ; Hashemi, S.

Multi-Objective clustering as the most important and fundamental unsupervised learning has been in the gravity of focus of quite a lot numbers of researchers over several decades. In this paper, we suggest a multi-objective clustering technique based on the notion of game theory. The presented method is designed to optimize two intrinsically conflicting objectives, named, compaction and equi-partitioning. The key contributions of the proposed approach is that the proposed method performs better off by utilizing the advantages of mixed strategies as well as those of pure ones, considering the existence of mixed Nash Equilibrium in every game. The approach known as Mixed Game Theoretic Kmeans offers the optimal solution in a very promising manner by optimizing both objectives simultaneously. The experimental results suggest that the proposed approach significantly outperforms other rival methods across real world and synthetic data sets.

Published in:

Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on

Date of Conference:

2-3 May 2012

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.