engleski

Subgroup discovery for actionable knowledge generation: defiences of classification rule learning and lessons learned

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 detecting individuals with high disease risk. The disadvantages of using standard classification rule learning for this task are discussed, and three subgroup discovery implementations are outlined. Case studies, a medical and two marketing ones, are used to present the lessons learned in solving problems requiring actionable knowledge generation.

actionable knowledge; subgroup discovery

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