Close category search window
 

Research on new data mining method based on hybrid genetic algorithm

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

2 Author(s)
Zhang Lianmei ; Comput. Sch., Wuhan Univ., Wuhan, China ; Jiang Xingjun

For classification problems in data mining based on the thought of combination classification method, this paper proposes a combination classification method of multiple decision trees, which was based on genetic algorithm. In the proposed combination classification method, multiple decision trees that adopt the method of probability measurement level output are parallel combined. Then genetic algorithm is used for the optimization of connection weight matrix in combination algorithm. Further more, two sets of simulation experiment data are used to test and evaluate the proposed combination classification method. Results of the experiments indicate that the proposed combination classification method has higher classification accuracy level than single decision tree. Moreover, it optimizes classification rules and sustains good interpretability for classification results.

Published in:
Computer Communication Control and Automation (3CA), 2010 International Symposium on  (Volume:1 )

Date of Conference: 5-7 May 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.