Reduction Algorithm Based On Rough Set Theory Knowledge Research

Rough set theory is emerging as a new tool for dealing with fuzzy and uncertain data. It is very efficient to analyse and process imprecise and imperfect data. It can find potential knowledge and rule from data. In recent years,it has been studied and applied in many fields such as machine learning,data mining and etc. In the research of rough set theory, there are some problems that need to be solved:(1) Data driving knowledge acquirement(2) The relationship between algebra view and information view based on rough set theory(3) Knowledge acquirement in incomplete information system directly(4) Develop granule computing model based on rough set theory(5) Incremental knowledge acquirementIn this paper, we discuss the problem (3), (4), (5), and develop a direct approach for incomplete information system, a granular computing model based on tolerance relation, a incremental attribute reduction algorithm.