Attribute reduction approaches for general relation decision systems
Propose the concept of general relation decision systems.Give an attribute reduction algorithm for consistent relation decision systems.Give an attribute reduction algorithm for inconsistent relation decision systems. This paper proposes the concept of general relation decision systems and studies attribute reduction algorithms for relation decision systems, which are generalization of decision tables. In our relation decision systems, both condition and decision attribute sets consist of general binary relations. Novel attribute reduction algorithms for consistent and inconsistent relation decision systems are derived, respectively. A data set from the UCI machine learning databases is used in the empirical study, the experimental results verify the effectiveness of the proposed algorithms. The results unify the earlier attribute reduction algorithms for decision tables.