RSD: Relational Subgroup Discovery through First-Order Feature Construction
نویسندگان
چکیده
Relational rule learning is typically used in solving classification and prediction tasks. However, relational rule learning can be adapted also to subgroup discovery. This paper proposes a propositionalization approach to relational subgroup discovery, achieved through appropriately adapting rule learning and first-order feature construction. The proposed approach, applicable to subgroup discovery in individualcentered domains, was successfully applied to two standard ILP problems (East-West trains and KRK) and a real-life telecommunications application.
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