Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Discovering associations with numeric variables
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Spatial Subgroup Mining Integrated in an Object-Relational Spatial Database
PKDD '02 Proceedings of the 6th European Conference 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
Interpreting PET Scans by Structured Patient Data: A Data Mining Case Study in Dementia Research
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
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
Relevancy in constraint-based subgroup discovery
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Guest editors' introduction: special issue of selected papers from ECML PKDD 2009
Data Mining and Knowledge Discovery
Guest editors' introduction: Special Issue from ECML PKDD 2009
Machine Learning
On Subgroup Discovery in Numerical Domains
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Different slopes for different folks: mining for exceptional regression models with cook's distance
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
From black and white to full color: extending redescription mining outside the Boolean world
Statistical Analysis and Data Mining
Subgroup discovery using bump hunting on multi-relational histograms
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
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Subgroup discovery is a Knowledge Discovery task that aims at finding subgroups of a population with high generality and distributional unusualness. While several subgroup discovery algorithms have been presented in the past, they focus on databases with nominal attributes or make use of discretization to get rid of the numerical attributes. In this paper, we illustrate why the replacement of numerical attributes by nominal attributes can result in suboptimal results. Thereafter, we present a new subgroup discovery algorithm that prunes large parts of the search space by exploiting bounds between related numerical subgroup descriptions. The same algorithm can also be applied to ordinal attributes. In an experimental section, we show that the use of our new pruning scheme results in a huge performance gain when more that just a few split-points are considered for the numerical attributes.