Zusammenfassung
In data mining, the quality of induced knowledge is
determined by several features. The focus has been
usually placed on accuracy, paying much less attention
to comprehensibility. In this paper, we present a
rule-based data mining system for classification. Our
main goal is the analysis of the trade-off between
accuracy and comprehensibility, but we approach
comprehensibility from a novel point of view: we are
interested in gaining insight into how the use of
logical operators affects comprehensibility. In
addition, we study the suitability of grammar-based
genetic programming for data mining
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