关键词: 粗糙集, 邻域关系, 约简, 决策表, 启发式算法

Abstract:

In view of the fact that the classical rough set theory has  difficulty  dealing  with  continuous data, a reduction method was proposed based on neighborhood relation in the decision table. By the definitions of neighborhood relation and neighborhood parameter, each object in the universe was assigned to  a neighborhood subset, called neighborhood granule, which could avoid the loss of information in the discretization process. The concepts of neighborhood positive region and neighborhood reduction were defined. The positive region monotonous principle was analyzed. Furthermore, the dependency function based on neighborhood relation was used to evaluate the significance of attributes and two heuristic attribute reduction algorithms were constructed. Theoretical analysis and an   example showed  that the reduction method was efficient and feasible.

Key words: rough sets, neighborhood relation, reduction, decision table, heuristic algorithm