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.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)