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Explanation Oriented Association Mining Using Rough Set Theory

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

Abstract

This paper presents a new philosophical view and methodology for data mining. A framework of explanation oriented data mining is proposed and studied with respect to association mining. The notion of conditional associations is adopted, which explicitly expresses the conditions under which an association occurs. To illustrate the basic ideas, the theory of rough sets is used to construct explanations.

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© 2003 Springer-Verlag Berlin Heidelberg

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Yao, Y.Y., Zhao, Y., Maguire, R.B. (2003). Explanation Oriented Association Mining Using Rough Set Theory. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_21

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  • DOI: https://doi.org/10.1007/3-540-39205-X_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

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