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RSD: Relational Subgroup Discovery through First-Order Feature Construction

Nada Lavrac, Filip Zelezny, Peter A/ Flach, RSD: Relational Subgroup Discovery through First-Order Feature Construction. Proceedings of the 12th International Conference on Inductive Logic Programming. ISBN 3-540-00567-6, pp. 149–165. July 2002. PDF, 228 Kbytes.

Abstract

Relational rule learning is typically used in solving classi- fication and prediction tasks. However, relational rule learning can be adapted also to subgroup discovery. This paper proposes a proposition- alization approach to relational subgroup discovery, achieved through appropriately adapting rule learning and first-order feature construction. The proposed approach, applicable to subgroup discovery in individual- centered domains, was successfully applied to two standard ILP problems (East-West trains and KRK) and a real-life telecommunications applica- tion.

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