By Topic

Pattern recognition system based on decision trees and fuzzy logic: Anti-HIV molecules application

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)
Kissi, M. ; Fac. des Sci., Dept. de Math. et Inf., Univ. Chouaib Doukkali, El Jadida, Morocco ; Ramdani, M. ; Cherqaoui, D.

Several works structure activity relationship (SAR) of anti-HIV molecules (Human Immunodeficiency Virus) were studied by different statistical methods and non-linear models (neural networks). But few studies have used the heuristic methods. In this work, we are interested to study this relationship by fuzzy logic and decision trees. The resulting model explain SAR with only tow rules described by three of 7 molecular descriptors. This rules generalize the 79 compounds studied. Decision trees show good performance in the learning and prediction phases.

Published in:

Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on

Date of Conference:

2-4 April 2009