Zhong, Ning; Dong, Juzhen Mining interesting rules in meningitis data by cooperatively using GDT-RS and RSBR. (English) Zbl 1048.68959 Chen, Ming-Syan (ed.) et al., Advances in knowledge discovery and data mining. 6th Pacific-Asia conference, PAKDD 2002, Taipei, Taiwan, May 6–8, 2002. Proceedings. Berlin: Springer (ISBN 3-540-43704-5). Lect. Notes Comput. Sci. 2336, 405-416 (2002). Summary: 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.For the entire collection see [Zbl 0992.68521]. MSC: 68U99 Computing methodologies and applications 68P15 Database theory 68P20 Information storage and retrieval of data 92C50 Medical applications (general) Keywords:Rough Sets; Meningitis Data Mining; Class Selection; Hybrid Systems Software:RSBR_ PDFBibTeX XMLCite \textit{N. Zhong} and \textit{J. Dong}, Lect. Notes Comput. Sci. 2336, 405--416 (2002; Zbl 1048.68959) Full Text: Link