Abstract
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.
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