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AbstractIn this paper, we propose a method for the evaluation of importance of rows for decision tables. It is based on indirect information about changes in the set of reducts after removing the considered row from the table. We also discuss results of computer experiments with decision tables from UCI Machine Learning Repository.
CitationAbouEisha H, Azad M, Moshkov M (2017) On Importance of Rows for Decision Tables. Lecture Notes in Computer Science: 376–383. Available: http://dx.doi.org/10.1007/978-3-319-60837-2_31.
SponsorsResearch reported in this publication was supported by King Abdullah University of Science and Technology (KAUST).
PublisherSpringer International Publishing
Conference/Event nameInternational Joint Conference on Rough Sets, IJCRS 2017