关键词: 模糊决策粗糙集,代价敏感,属性约简

Abstract: Aiming at the cost problem that generally exists in desicion-making,on the basis of fuzzy theory and decision theoretic rough sets,we studied the method of cost sensitive attribute reduction.We introduced the total cost including misclassification cost and test cost into attribute reduction for fuzzy decision theoretic rough sets (FDTRS).Thus the target of reduction is not only to considere the size of positive region,but also to find the optimal subset of attributes with the minimum total cost.We proposed a cost sensitive attribute reduction (named as COSAR) algorithm for FDTRS.The algorithm uses a heuristic method to search the optimal subset.We provided the procedure of the algorithm and compared the performance of the algorithm with the existing FDTRS attribute reduction algorithm,called QuickReduct.The experimental results show that COSAR algorithm has stronger attribute reduction capability,lower total classification cost,shorter running time than QuickReduct algorithm,and with the increasing of test samples,the difference of total classification cost between two methods is growing larger.

Key words: Fuzzy decision theoretic rough sets(FDTRS),Cost sensitive,Attribute reduction