Subgroup discovery techniques and applications

Authors:
Nada Lavrač
Affiliations:
Jožef Stefan Institute, Ljubljana, Slovenia
Venue:
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Year:
2005

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Abstract

This paper presents the advances in subgroup discovery and the ways to use subgroup discovery to generate actionable knowledge for decision support. Actionable knowledge is explicit symbolic knowledge, typically presented in the form of rules, that allow the decision maker to recognize some important relations and to perform an appropriate action, such as planning a population screening campaign aimed at detecting individuals with high disease risk. Two case studies from medicine and functional genomics are used to present the lessons learned in solving problems requiring actionable knowledge generation for decision support.