Referenced Items are not available for this document.
The decision tree based on the k-means algorithm has recently been proposed. However, the drawback of the k-means algorithm is that the users must determine the number of branches for each node before the decision tree is designed. The users are usually hard to determine the number of branches for each node. In this study, the new decision tree with variable-branches is proposed. The genetic algorithm is proposed to determine the number of branches for each node in the new decision tree. Thus, the proposed new decision tree approaches to near-optimization.
Published in:
Computer Communication Control and Automation (3CA), 2010 International Symposium on
(Volume:1
)
Date of Conference: 5-7 May 2010
- Page(s):
- 115 - 118
- Print ISBN:
- 978-1-4244-5565-2
- INSPEC Accession Number:
- 11460744
- Conference Location :
- Tainan
- Digital Object Identifier :
- 10.1109/3CA.2010.5533877
- Product Type:
- Conference Publications
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.
