Detection and Management of Concept Drift
Mak, Lee-Onn and Krause, Paul (2006) Detection and Management of Concept Drift Proceedings of the Fifth International Conference on Machine Learning and Cybernetics. pp. 3486-3491.
SRF002343.pdf - Published Version
The ability to correctly detect the location and derive the contextual information where a concept begins to drift is essential in the study of domains with changing context. This paper proposes a Top-down learning method with the incorporation of a learning accuracy mechanism to efficiently detect and manage context changes within a large dataset. With the utilisation of simple search operators to perform convergent search and JBNC with a graphical viewer to derive context information, the identified hidden context are shown with the location of the disjoint points, the contextual attributes that contribute to the concept drift, the graphical output of the true relationships between these attributes and the Boolean characterisation which is the context.
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|Divisions:||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research|
|Depositing User:||Melanie Hughes|
|Date Deposited:||23 Sep 2010 09:01|
|Last Modified:||23 Sep 2013 18:38|
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