Abstract: Through decision table transformation, the rules were mapped to cloud vectors. The equivalence relations betwecn the rules were reckoned using the similarity between the cloud vectors' digital characteristics. On this basis, a rules reduction algorithm for decision table based on cloud model was proposed. It not only resolves the problem that the ectuivalence relation based on rough set theory doesn't distinguish the similar relationship because it requires matcking strictly each attribute, but also overcomes the shortcomings that the equivalence relation based on fuzzy set relics on the priori knowledge and considers inadequate to the random distribution of attributes. Experiments show the algorithm has high performance.

Key words: Rough set, Decision table, Cloud model, Rules reduction, Equivalence relation