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.
Highlights
Rough set theory, a mathematical tool for dealing with vagueness and uncertainty, was introduced by Pawlak in 19821
Classical rough sets have been extended to several general models, such as covering rough set model[7], fuzzy rough set model[8], variable precision rough set model[9], generalized rough set model[10], probabilistic rough set model[11], etc
Li et al presented an incremental method of updating decision rules when multi-attributes are deleted or added simultaneously under rough set based on the characteristic relation[16]
Summary
A mathematical tool for dealing with vagueness and uncertainty, was introduced by Pawlak in 19821. Li et al presented an incremental method of updating decision rules when multi-attributes are deleted or added simultaneously under rough set based on the characteristic relation[16]. We discusses the approaches for incrementally acquiring approximations based on the grade indiscernibility relation when the information system changes. Due to these approaches are used in succession, they can effectively updated approximations when any possible changes in the information system occur. The remainders of the sections are focused on the approaches for incrementally updating approximations based on the grade indiscernibility relation when the information system varies with time. We conclude the work of this paper and preview the further work
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