Ning, Zhong; Dong, Ju-Zhen; Ohsuga, Setsuo Meningitis data mining by cooperatively using GDT-RS and RSBR. (English) Zbl 1053.68099 Pattern Recognit. Lett. 24, No. 6, 887-894 (2003). Summary: This paper describes an application of two rough sets based systems, namely Generalized Distribution Table and Rough Set (GDT-RS) and Rough Sets with Boolean Reasoning (RSBR) respectively, for mining if-then rules in a meningitis dataset. GDT-RS is a soft hybrid induction system, and RSBR is used for discretization of real valued attributes as a pre-processing 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. Cited in 2 Documents MSC: 68T30 Knowledge representation 68T05 Learning and adaptive systems in artificial intelligence Keywords:Rough sets; Meningitis data mining; Class selection; Hybrid systems Software:RSBR_ PDFBibTeX XMLCite \textit{Z. Ning} et al., Pattern Recognit. Lett. 24, No. 6, 887--894 (2003; Zbl 1053.68099) Full Text: DOI