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Data Mining: Foundations and Practice pp 315–337Cite as

Classes of Association Rules: An Overview

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 118))

Summary

Chapter concerns theoretical foundations of association rules. We deal with more general rules than the classical association rules related to market baskets are. Various theoretical aspects of association rules are introduced and several classes of association rules are defined. Implicational and double implicational rules are examples of such classes. It is shown that there are practically important theoretical results related to particular classes. Results concern deduction rules in logical calculi of association rules, fast evaluation of rules corresponding to statistical hypotheses tests, missing information and definability of association rules in classical predicate calculi.

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References

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Author information

Authors and Affiliations

  1. University of Economics, Prague, nám. W. Churchilla 4, 130 67, Praha, Czech Republic

    Jan Rauch

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  1. Jan Rauch
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Editor information

Editors and Affiliations

  1. Department of Computer Science, San Jose State University, San Jose, CA, 95192, USA

    Tsau Young Lin

  2. Department of Computer Science and Information Systems, Kennesaw State University, Building 11, Room 3060 1000 Chastain Road, Kennesaw, GA, 30144, USA

    Ying Xie

  3. Department of Computer Science, The University at Stony Brook, Stony Brook, New York, 11794-4400, USA

    Anita Wasilewska

  4. Institute of Information Science, Academia Sinica, No 128, Academia Road, Section 2 Nankang, Taipei, 11529, Taiwan

    Churn-Jung Liau

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Rauch, J. (2008). Classes of Association Rules: An Overview. In: Lin, T.Y., Xie, Y., Wasilewska, A., Liau, CJ. (eds) Data Mining: Foundations and Practice. Studies in Computational Intelligence, vol 118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78488-3_19

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  • DOI: https://doi.org/10.1007/978-3-540-78488-3_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78487-6

  • Online ISBN: 978-3-540-78488-3

  • eBook Packages: EngineeringEngineering (R0)

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