Abstract
In this paper, we propose a complex learning system for data analysis (DP) that is based on behavior factor. This system combines features of both rule-based systems (RBS) and rule-based DP framework. We have identified and analyzed the properties that distinguish behavior factor and rules from data for better determining the most components of the proposed system. For representing domain behavior factor, we investigated a uniform and unified rule representation form based on the creation of the environment component that stored information especially for the management of rule and its quality. Besides dealing with some limitations of currently RBS and BFS cited above, the system through the case study allows us to observe many advantages.
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© 2013 Springer-Verlag London
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Guan, W. (2013). A Complex Learning System for Behavior Factor Based Data Analysis. In: Zhong, Z. (eds) Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012. Lecture Notes in Electrical Engineering, vol 220. Springer, London. https://doi.org/10.1007/978-1-4471-4844-9_103
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DOI: https://doi.org/10.1007/978-1-4471-4844-9_103
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