Neural-Based Learning Classifier Systems

12 years 9 months ago
Neural-Based Learning Classifier Systems
UCS is a supervised learning classifier system that was introduced in 2003 for classification in data mining tasks. The representation of a rule in UCS as a univariate classification rule is straightforward for a human to understand. However, the system may require a large number of rules to cover the input space. Artificial neural networks, on the other hand, normally provide a more compact representation. However, it is not a straightforward task to understand the network. In this paper, we propose a novel way to incorporate neural networks into UCS. The approach offers a good compromise between compactness, expressiveness, and accuracy. By using a simple artificial neural network as the classifier's action, we obtain a more compact population size, better generalization, and the same or better accuracy, while maintaining a reasonable level of expressiveness. We also apply negative correlation learning (NCL) during the training of the resultant neural network ensemble. NCL is sh...
Hai Huong Dam, Hussein A. Abbass, Chris Lokan, Xin
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TKDE
Authors Hai Huong Dam, Hussein A. Abbass, Chris Lokan, Xin Yao
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