This paper discusses actionable knowledge generation. Actionable knowledge is explicit symbolic knowledge, typically presented in the form of rules, that allows the decision maker to recognize some important relations and to perform an action, such as targeting a direct marketing campaign, or planning a population screening campaign aimed at targeting individuals with high disease risk. The disadvantages of using standard classification rule learning for this task are discussed, and a subgroup discovery approach proposed. This approach uses a novel definition of rule quality which is extensively discussed. © 2002 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Gamberger, D., & Lavrač, N. (2002). Generating actionable knowledge by expert-guided subgroup discovery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2431 LNAI, pp. 163–175). Springer Verlag. https://doi.org/10.1007/3-540-45681-3_14
Mendeley helps you to discover research relevant for your work.