Abstract
A rule in a Deterministic Information System (DIS) is often defined by an implication τ such that both support(τ) ≥ α and accuracy(τ) ≥ β hold for the threshold values α and β. In a Non-deterministic Information System (NIS), there are derived DISs due to the information incompleteness. The definition of a rule in a DIS is extended to the lower and upper approximations of a rule in a NIS. This definition explicitly handles non-deterministic information and incomplete information. To implement the utility programs for two approximations, Apriori algorithm is extended. Even though the number of derived DISs increases in exponential order, this extended algorithm does not depend upon the number of derived DISs. A prototype system is implemented, and this system is applied to some data sets.
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Sakai, H., Ishibashi, R., Nakata, M. (2008). Lower and Upper Approximations of Rules in Non-deterministic Information Systems. In: Chan, CC., Grzymala-Busse, J.W., Ziarko, W.P. (eds) Rough Sets and Current Trends in Computing. RSCTC 2008. Lecture Notes in Computer Science(), vol 5306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88425-5_31
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DOI: https://doi.org/10.1007/978-3-540-88425-5_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88423-1
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