Rule induction with CN2: some recent improvements
EWSL-91 Proceedings of the European working session on learning on Machine learning
Machine Learning - special issue on inductive logic programming
Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Robust classification systems for imprecise environments
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Mastering Data Mining: The Art and Science of Customer Relationship Management
Mastering Data Mining: The Art and Science of Customer Relationship Management
Inductive logic programming for knowedge discovery in databases
Relational Data Mining
Three companions for data mining in first order logic
Relational Data Mining
Machine Learning
Machine Learning
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Adapting classification rule induction to subgroup discovery
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Subgroup Discovery with CN2-SD
The Journal of Machine Learning Research
Expert-guided subgroup discovery: methodology and application
Journal of Artificial Intelligence Research
Active subgroup mining: a case study in coronary heart disease risk group detection
Artificial Intelligence in Medicine
Editorial: Data Mining Lessons Learned
Machine Learning
A probabilistic classifier system and its application in data mining
Evolutionary Computation
Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection
Expert Systems with Applications: An International Journal
Tight Optimistic Estimates for Fast Subgroup Discovery
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Expert Systems with Applications: An International Journal
CSM-SD: Methodology for contrast set mining through subgroup discovery
Journal of Biomedical Informatics
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Improved Comprehensibility and Reliability of Explanations via Restricted Halfspace Discretization
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
On subgroup discovery in numerical domains
Data Mining and Knowledge Discovery
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
A distance-based approach for action recommendation
ECML'05 Proceedings of the 16th European conference on Machine Learning
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This paper presents 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 allows the decision maker to recognize some important relations and to perform an appropriate action, such as targeting a direct marketing campaign, or planning a population screening campaign aimed at detecting individuals with high disease risk. Different subgroup discovery approaches are outlined, and their advantages over using standard classification rule learning are discussed. Three case studies, a medical and two marketing ones, are used to present the lessons learned in solving problems requiring actionable knowledge generation for decision support.