Incremental update of rough set approximation under the grade indiscernibility relation

Abstract

The incremental updating of lower and upper approximations under the variation of information systems is an important issue in rough set theory. Many incremental updating approaches with respect to different kinds of indiscernibility relations have been proposed. The grade indiscernibility relation is a fuzzification of classical Pawlak's indiscernibility relation which can characterize the similarity between objects more precisely. Based on fuzzy rough set model, this paper discusses the approaches for dynamically acquiring of the upper and lower approximations with respect to the grade indiscernibility relation when adding and removing an attribute or an object, and changing the attribute value of the object, respectively. Since the approaches are used in succession, they make the approximations can be updated correctly and effectively when any kind of possible change in the information system. Finally, extensive experiments on data sets from University of California, Irvine (UCI) show that the incremental methods effectively reduce the computing time in comparison with the traditional non-incremental method.

Information Fusion in a Multi-Source Incomplete Information System Based on Information Entropy

“…Huang et al [26] proposed a novel method for tourism analysis with multiple outcome capability based on rough set theory. Luo et al [27] studied incremental update of rough set approximation under the grade indiscernibility relation. Yuan et al [28] considered multi-sensor information fusion based on rough set theory.…”