关键词: 决策粗糙集模型, 属性约简, 风险最小化

Abstract: Attribute reductions in decision-theoretic rough set model are generally defined based on keeping the positive region unchanged or the non-negative region unchanged. Because the positive region and non-negative region are preferred to the negative region by people in these definitions, it is difficult to evaluate and interpret this kind of subjective reductions. In decision-theoretic rough set model, all regions are determined according to the Bayesian decision procedure, and the minimum cost is considered as the principle in the decision procedure. Based on the minimum cost of decisions for the decision table, an attribute reduction is proposed. The cost of decisions which are decided based on the reduction is minimal. The definition is easier to understand and interpret than those region-based reductions.

Key words: decision-theoretic rough set model, attribute reduction, minimum cost