Abstract
The aim of this paper is to generalize the concept of association rules for interval-valued fuzzy sets. Interval-valued fuzzy sets allow for intervals of membership degrees to be assigned to each element of the universe. These intervals may be interpreted as partial information where the exact membership degree is not known. The paper provides a generalized definition of support and confidence, which are the most commonly known measures of quality of a rule.
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Authors acknowledge support by project “LQ1602 IT4Innovations excellence in science” and by GAČR 16-19170S.
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Murinová, P., Pavliska, V., Burda, M. (2018). Association Analysis on Interval-Valued Fuzzy Sets. In: Torra, V., Narukawa, Y., Aguiló, I., González-Hidalgo, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2018. Lecture Notes in Computer Science(), vol 11144. Springer, Cham. https://doi.org/10.1007/978-3-030-00202-2_8
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