Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
A tight analysis of the greedy algorithm for set cover
Journal of Algorithms
A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
Efficient mining of association rules using closed itemset lattices
Information Systems
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Subgroup Discovery with CN2-SD
The Journal of Machine Learning Research
The Journal of Machine Learning Research
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
SD-map: a fast algorithm for exhaustive subgroup discovery
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
A generic algorithm for generating closed sets of a binary relation
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
Adverse drug reaction mining in pharmacovigilance data using formal concept analysis
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Subgroup discovery for election analysis: a case study in descriptive data mining
DS'10 Proceedings of the 13th international conference on Discovery science
Fast and memory-efficient discovery of the top-k relevant subgroups in a reduced candidate space
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
Secure Distributed Subgroup Discovery in Horizontally Partitioned Data
Transactions on Data Privacy
An enhanced relevance criterion for more concise supervised pattern discovery
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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Subgroup discovery is a local pattern discovery task, in which descriptions of subpopulations of a database are evaluated against some quality function. As standard quality functions are functions of the described subpopulation, we propose to search for equivalence classes of descriptions with respect to their extension in the database rather than individual descriptions. These equivalence classes have unique maximal representatives forming a closure system. We show that minimum cardinality representatives of each equivalence class can be found during the enumeration process of that closure system without additional cost, while finding a minimum representative of a single equivalence class is NP-hard. With several real-world datasets we demonstrate that search space and output are significantly reduced by considering equivalence classes instead of individual descriptions and that the minimum representatives constitute a family of subgroup descriptions that is of same or better expressive power than those generated by traditional methods.