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Upper Bounds on Minimum Cardinality of Exact and Approximate Reducts
Conference proceeding   Peer reviewed

Upper Bounds on Minimum Cardinality of Exact and Approximate Reducts

Igor Chikalov, Mikhail Moshkov and Beata Zielosko
ROUGH SETS AND CURRENT TRENDS IN COMPUTING, PROCEEDINGS, Vol.6086, pp.412-417
Lecture Notes in Artificial Intelligence
01/01/2010
DOI: https://doi.org/10.1007/978-3-642-13529-3_44

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Information Systems Computer Science, Theory & Methods Science & Technology Technology
In the paper, we consider the notions of exact and approximate decision reducts for binary decision tables. We present upper bounds on minimum cardinality of exact and approximate reducts depending on the number of rows (objects) in the decision table. We show that the bound for exact reducts is unimprovable in the general case, and the bound for approximate reducts is almost unimprovable in the general case.

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