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Using selective memory to track concept drift effectively

Lazarescu, Mihai M. and Venkatesh, Svetha 2003, Using selective memory to track concept drift effectively, in IASTED 2003 : Proceedings of the IASTED International Conference on Intelligent Systems and Control, ACTA Press, Anaheim, Calif., pp. 14-19.

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Title Using selective memory to track concept drift effectively
Author(s) Lazarescu, Mihai M.
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name IASTED International Conference on Intelligent Systems and Control ( Salzburg, Austra)
Conference location Salzburg, Austria
Conference dates 25-27 Jun. 2003
Title of proceedings IASTED 2003 : Proceedings of the IASTED International Conference on Intelligent Systems and Control
Editor(s) Hamza, M. H.
Publication date 2003
Conference series IASTED International Conference on Intelligent Systems and Control
Start page 14
End page 19
Total pages 6
Publisher ACTA Press
Place of publication Anaheim, Calif.
Keyword(s) data Mining
knowledge acquisition
machine Learning
Summary In this paper we describe a supervised learning algorithm that uses selective memory to track concept drift. Unlike previous methods to track concept drift that use window heuristics to adapt to changes, we present an improved approach that discriminates between the instances observed. The advantage of this method is that it allows the system to both adapt to and track drift more accurately as well as filter the noise in the data more effectively. We present the algorithm and compare its performance with FLORA a well known concept drift tracking algorithm.
ISBN 9780889863552
0889863555
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2003, ACTA Press
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044644

Document type: Conference Paper
Collection: School of Information Technology
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