Subgroup discovery using bump hunting on multi-relational histograms

Authors:
Radomír Černoch;Filip Železný
Affiliations:
Faculty of Electrical Engineering, Department of Cybernetics, Intelligent Data Analysis Research Lab, Czech Technical University, Czech;Faculty of Electrical Engineering, Department of Cybernetics, Intelligent Data Analysis Research Lab, Czech Technical University, Czech
Venue:
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Year:
2011

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Abstract

We propose an approach to subgroup discovery in relational databases containing numerical attributes. The approach is based on detecting bumps in histograms constructed from substitution sets resulting from matching a first-order query against the input relational database. The approach is evaluated on seven data sets, discovering interpretable subgroups. The subgroups' rate of survival from the training split to the testing split varies among the experimental data sets, but at least on three of them it is very high.