Rough computational methods for information systems
Artificial Intelligence
Rough Sets: Mathematical Foundations
Rough Sets: Mathematical Foundations
Tabu search for attribute reduction in rough set theory
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Efficient attribute reduction based on discernibility matrix
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Fast knowledge reduction algorithms based on quick sort
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
New reduction algorithm based on decision power of decision table
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Fundamenta Informaticae
Normalized Decision Functions and Measures for Inconsistent Decision Tables Analysis
Fundamenta Informaticae
On a Criterion of Similarity between Partitions Based on Rough Set Theory
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
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This paper focuses on rough set theory which provides mathematical foundations of set-theoretical approximation for concepts, as well as reasoning about data. Also presented in this paper is the concept of relative reducts which is one of the most important notions for rule generation based on rough set theory. In this paper, from the viewpoint of approximation, the authors introduce an evaluation criterion for relative reducts using roughness of partitions that are constructed from relative reducts. The proposed criterion evaluates each relative reduct by the average of coverage of decision rules based on the relative reduct, which also corresponds to evaluate the roughness of partition constructed from the relative reduct,