Abstract
Association rules in data mining are considered from a point of view of conditional logic and rough sets. In our previous work, given an association rule in some fixed database, its corresponding Kripke model was formulated. Then, two difficulties in the formulation were pointed out: limitation of the form of association rules and limited formulation of the models themselves. To resolve the defects, Chellas’s conditional logic was introduced and thereby, the class of conditionals in conditional logic can be naturally regarded as containing the original association rules. In this paper, further, an extension of conditional logic is introduced for dealing with association rules with intermediate values of confidence based on the idea of fuzzy-measure-based graded modal logic.
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Murai, T., Nakata, M., Sato, Y. (2001). A Note on Conditional Logic and Association Rules. In: Terano, T., Ohsawa, Y., Nishida, T., Namatame, A., Tsumoto, S., Washio, T. (eds) New Frontiers in Artificial Intelligence. JSAI 2001. Lecture Notes in Computer Science(), vol 2253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45548-5_52
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DOI: https://doi.org/10.1007/3-540-45548-5_52
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