Mining Interesting Rules in Meningitis Data by Cooperatively Using GDT-RS and RSBR

Authors:
Ning Zhong;Juzhen Dong
Affiliations:
-;-
Venue:
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Year:
2002

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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.