A Model Of Warning About Teaching Based On Rough Set

Teaching warning as an important measure to ensure the quality of teaching in collegeteaching is particularly important under the backgroud that colleges and universities are trainingtalent on a large scale. The traditional teaching warning rely on simple statistical data such asexcel spreadsheets. It has the disadvantages of lag, has cost the human fallibility. As theinformation science and technology is rapid development, it is necessary to find the a automatedway for teaching warning.As a relatively new tools to deal with uncertain information and fuzzyinformation, Rough set theory has many advantages, such as it does’t need any priori knowledgefor data mining, it is easy to understand and it is suitable for concurrent processing. In recentyears Rough sets has been successfully applicated in different industries around the world andpeople has obtained good returns,which provides theoretical basis and experience for ourautomated warning.The ideal that applying Rough set theory to the teaching warning has come into being..Thework to research in this subject is as follows:Firstly, briefly this paper introduces the rough settheory and expounds the present situation of the research at home and abroad and reviews thesignificance、the feasibility and necessity of the research in this paper. This paper also introducesthe basic concepts of classic set theory such as equivalent class, introduces the basic knowledgeand necessary related definitions of rough set theory. Secondly, this paper describes and analysisthe algorithms which are used in Rough set theory in detail. The algorithms include attributereduction algorithm based on importance of attribute、algorithm of attribute reduction based ondiscernibility matrix、attribute value reduction algorithm based on heuristic function and thediscretization algorithm of continuous attributes.Then this paper give the system model andrespectively analysis of the system modules in detail and shows the flowcharts of them.Finally,this paper does experiment through the real data. The experiment obtains satisfactoryresults which make the application of teaching warning model based on rough set has feasibility.