Abstract
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. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Chikalov, I., Moshkov, M., & Zielosko, B. (2010). Upper bounds on minimum cardinality of exact and approximate reducts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6086 LNAI, pp. 412–417). https://doi.org/10.1007/978-3-642-13529-3_44
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