Dynamics approximate rule mining inference approach based on rough set theory
一种基于粗集理论的动态近似规则挖掘推理方法

Based on rough set theory, a rule inference approach of integrating the importance of attributes with the emergence frequency of attribute value is proposed. After the analysis of the principle of "fall one or leave", it is pointed out that the number of rules in rule inference would be variable. A method is suggested to decide whether a rule is needed or not by its emergence frequency in the inference process, so the number of the rules is dynamic. The dynamic rule is proved not to increase in the process. The results of examples show the efficiency of the approach.