|Title:||Simple data filtering in rough set systems|
Ivo Düntsch ,
Dept of Computer Science ,
Brock University ,
St Catherines, Ontario, L2S 3A1, Canada
Günther Gediga , Institut für Evaluation und Marktanalysen; Brinkstr. 19; D-49143 Jeggen; Germany
(Equal authorship implied)
|Status:||International Journal of Approximate Reasoning 18 (1998), 93-106|
In symbolic data analysis, high granularity of information may lead to rules
based on a few cases only for which there is no evidence that they are not
due to random choice, and thus have a doubtful validity.
We suggest a simple way to improve the statistical strength of rules obtained by rough set data analysis by identifying attribute values and investigating the resulting information system. This enables the researcher to reduce the granularity within attributes without assuming external structural information such as probability distributions or fuzzy membership functions.
|View technical report version|