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

Improved Clustering Approach based on Fuzzy Feature Selection

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

4 Author(s)
Naijun Wu ; Shanghai Univ. of Finance & Econ., Shanghai ; Xiuyun Li ; Jie Yang ; Peng Liu

Clustering is one of the most heated topics in data mining research. In traditional clustering algorithms, each feature is treated equally and each one does the same contribution to clustering. As a matter of fact, redundant and unrelated features may disturb the clustering result. This paper proposed a fuzzy feature selection strategy to improve the clustering algorithm. The strategy is based on measuring 'Feature Important Factor' (FIF) to describe the contribution of each feature to the clustering, and makes use of the FIF to get the generalized weight of the contribution of each feature to clustering. In this strategy, the FIF and clustering result are iteratively modified until the result is stable, for the purpose of improving the clustering result. The experiment of K-means algorithm proves that, the strategy of fuzzy feature selection proposed by this paper, can improve the clustering result effectively.

Published in:

Service Systems and Service Management, 2007 International Conference on

Date of Conference:

9-11 June 2007

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.