Abstract
This paper describes an application of two rough sets based systems, namely GDT-RS and RSBR respectively, for mining if-then rules in a meningitis dataset. GDT-RS (Generalized Distribution Table and Rough Set) is a soft hybrid induction system, and RSBR (Rough Sets with Boolean Reasoning) is used for discretization of real valued attributes as a preprocessing step realized before the GDT-RS starts.We argue that discretization of continuous valued attributes is an important pre-processing step in the rule discovery process. We illustrate the quality of rules discovered by GDT-RS is strongly affected by the result of discretization.
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Zhong, N., Dong, JZ., Ohsuga, S. (2001). Meningitis Data Mining by Cooperatively Using GDT-RS and RSBR. In: Terano, T., Ohsawa, Y., Nishida, T., Namatame, A., Tsumoto, S., Washio, T. (eds) New Frontiers in Artificial Intelligence. JSAI 2001. Lecture Notes in Computer Science(), vol 2253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45548-5_75
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DOI: https://doi.org/10.1007/3-540-45548-5_75
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