Name
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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Year | DOI | Venue |
|---|---|---|
2001 | 10.1016/S0167-8655(02)00200-3 | Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining |
Keywords | DocType | Volume |
generalized distribution table,soft hybrid induction system,rough set,boolean reasoning,rough sets,meningitis data mining,mining if-then rule,generalized distribution,preprocessing step,rule discovery process,important pre-processing step,meningitis dataset,pre-processing step,data mining | Conference | 24 |
Issue | ISSN | Citations |
6 | 0167-8655 | 2 |
PageRank | References | Authors |
0.52 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ning Zhong | 1 | 2907 | 300.63 |
| Juzhen Dong | 2 | 214 | 17.05 |
| Setsuo Ohsuga | 3 | 960 | 222.02 |