Optimal Subgroup Discovery in Purely Numerical Data [chapter]

Alexandre Millot, Rémy Cazabet, Jean-François Boulicaut
2020 Lecture Notes in Computer Science  
Subgroup discovery in labeled data is the task of discovering patterns in the description space of objects to find subsets of objects whose labels show an interesting distribution, for example the disproportionate representation of a label value. Discovering interesting subgroups in purely numerical data -attributes and target label -has received little attention so far. Existing methods make use of discretization methods that lead to a loss of information and suboptimal results. This is the
more » ... e for the reference algorithm SD-Map*. We consider here the discovery of optimal subgroups according to an interestingness measure in purely numerical data. We leverage the concept of closed interval patterns and advanced enumeration and pruning techniques. The performances of our algorithm are studied empirically and its added-value w.r.t. SD-Map* is illustrated.
doi:10.1007/978-3-030-47436-2_9 fatcat:4q6tontjc5dubg7kpuqwoljqy4