关键词: 邻域粗糙集, 邻域信息熵, 不确定性度量, 信息系统, 近似精度

Abstract: In view of the fact that the uncertainty measures of classical rough set theory are difficult to be suitable for neighborhood rough set model, this paper proposes an uncertainty measurement method based on information  entropy and neighborhood rough sets. By the definitions of neighborhood relation, each object in the universe is    assigned with a neighborhood subset, called neighborhood granule. Some uncertainty measures of neighborhood granule are defined, including approximate accuracy, information entropy and weighted information entropy in the neighborhood system. Furthermore, this paper presents the axiomatic concept of measure, and proves that the three measures are axiomatic uncertainty measures. This paper also gives the maximum and minimum of these measures and proves their monotonicities. Theoretical analysis and experiments show that the information entropy measure in the neighborhood system is better than the approximate accuracy measure.

Key words: neighborhood rough sets, neighborhood information entropy, uncertainty measure, information system, approximation accuracy