An algorithm for attribute reduction based on classification of condition attributes in rough set

摘要

Attribute reduction can remove redundant attributes and improve the efficiency of decision making in the case of keeping the classification of research objects. This paper researches attributes reduction of rough set theory. Based on the definition of core in rough set attribute reduction, this paper classifies condition attributes and extracts significant and insignificant attributes. On this basis, combining with Pawlak's attribute reduction method, this paper puts forward an algorithm for attribute reduction based on classification of condition attributes. The experimental results show that the algorithm is verified to be more feasible and effective.