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International Conference on Inductive Logic Programming

ILP 2011: Inductive Logic Programming pp 76–90Cite as

Subgroup Discovery Using Bump Hunting on Multi-relational Histograms

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7207))

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.

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, Department of Cybernetics, Intelligent Data Analysis Research Lab, Czech Technical University, Czech

    Radomír Černoch & Filip Železný

Authors
  1. Radomír Černoch
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  2. Filip Železný
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Imperial College London, 180 Queen’s Gate, SW7 2AZ, London, UK

    Stephen H. Muggleton  & Alireza Tamaddoni-Nezhad  & 

  2. Dipartimento di Informatica, Università degli Studi di Bari “Aldo Moro”, Via E. Orabona, 4, 70125, Bari, Italy

    Francesca A. Lisi

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Černoch, R., Železný, F. (2012). Subgroup Discovery Using Bump Hunting on Multi-relational Histograms. In: Muggleton, S.H., Tamaddoni-Nezhad, A., Lisi, F.A. (eds) Inductive Logic Programming. ILP 2011. Lecture Notes in Computer Science(), vol 7207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31951-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-31951-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31950-1

  • Online ISBN: 978-3-642-31951-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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