By Topic

An efficient visual classification based approach to Decision Tree construction

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)
Rahman, T. ; Dept. of Inf. Eng., Hiroshima Univ., Hiroshima, Japan ; Harada, K.

Decision Tree (DT) analysis has emerged over the decades as an effective tool in classification or prediction. Since the publication of the first comprehensive and authoritative book on decision tree analysis by Howard Raiffa in 1968, its applications to a variety of problems from numerous disciplines have grown enormously. However, most of the methods for DT construction have some pitfalls including binary split points of numeric attributes instead of arbitrary splitting, involvement of users with prior domain knowledge to construct DT and finally the absence of training data visualization which this paper aims to remove. Besides we have proposed how the constructed DT can be applied for the adaptive interview process.

Published in:

Advanced Communication Technology (ICACT), 2012 14th International Conference on

Date of Conference:

19-22 Feb. 2012