Abstract
Approximation region-based decision tables are tabular specifications of three, in general uncertain, decision rules corresponding to rough approximation regions: positive, boundary and negative regions. The focus of the paper is on the extraction of such decision tables from data, their relationship to conjunctive rules and probabilistic assessment of decision confidence. The theoretical framework of the paper is a variable precision model of rough sets.
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Ziarko, W. (1998). Approximation Region-Based Decision Tables. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_25
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DOI: https://doi.org/10.1007/3-540-69115-4_25
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