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Association Rule Interestingness: Measure and Statistical Validation

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Quality Measures in Data Mining

Part of the book series: Studies in Computational Intelligence ((SCI,volume 43))

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Author information

Authors and Affiliations

  1. ERIC, University of Lyon 2, France

    Stephane Lallich

  2. TAO-Inria, LRI, University of Paris-Sud, Orsay, France

    Olivier Teytaud

  3. ERIC, University of Lyon 2, France

    Elie Prudhomme

Authors
  1. Stephane Lallich
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  2. Olivier Teytaud
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  3. Elie Prudhomme
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Editor information

Editors and Affiliations

  1. LINA-CNRS FRE 2729, Ecole polytechnique de l'université de Nantes, Rue Christian-Pauc-La Chantrerie, 60601, 44306, NANTES Cedex 3, France

    Fabrice J. Guillet

  2. Department of Computer Science, University of Regina, SK S4S 0A2, Regina, Canada

    Howard J. Hamilton

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Lallich, S., Teytaud, O., Prudhomme, E. (2007). Association Rule Interestingness: Measure and Statistical Validation. In: Guillet, F.J., Hamilton, H.J. (eds) Quality Measures in Data Mining. Studies in Computational Intelligence, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44918-8_11

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  • DOI: https://doi.org/10.1007/978-3-540-44918-8_11

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  • Online ISBN: 978-3-540-44918-8

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