Theories Related To Knowledge Discovery In Variable Universe Information Tables

In the process of data analysis,some information granules are usually induced from the information table according to certain rules,and then the corresponding granule computing model is established to deal with the corresponding data problems.Rough set is a very important granular computing model,which has a good e?ect on information processing and knowledge discovery.At present,scholars regard all objects in the information table as a discussion universe,and then build various rough set models.However,in many data problems,it makes more sense to choose as an universe the parts of the information table that are useful to us or that meet our practical needs.Therefore,in order to make up for the shortcomings of the traditional model,this paper studies the information table and the rough set model of the variable universe from the perspective of the variable universe.This paper discusses related theories of knowledge discovery based on variable universe information table,which mainly includes three parts:In the first part,based on the classical information table and according to the idea of variable universe,a rough set model based on variable universe information table was established,and the properties of the approximate set,attribute reduction,and maximum part of the universe of the model were studied.In the second part,a fuzzy rough set model based on variable universe is proposed,and the properties of its upper and lower approximation operators are discussed.The operational properties of fuzzy rough sets with variable universe are also studied.In the third part,from the perspective of numerical description,the number of information granules in the variable universe information table,the basis and dimension of information granule space,and the number of rough sets,the basis and dimension of rough set space,and the approximate properties of information granules in the variable universe based rough set model were studied.