The Application Of Rough Set Attirbute Model And Rough Set Clustering In English Scores

As we all know, English is the first language of the world, which is one of theworld’s currently the most common language. English is a door leading to the world,after China entered the World Trade Organization, the use of English is more widelyused. From the perspective of the world, the number of people speaking English hasexceeded and it is larger than any other number of other languages, and a third of theworld’s population speak English. After China’s reform and opening to the world, wemust learn the common language of the world, English as the most widely popularlanguage, it plays an important role in our learning and work.Data mining is a comprehensive discipline, which has a lot of applications inmany research fields. In this paper, the use of data mining method of rough set theoryand knowledge related clusters.In this paper, it used data mining algorithms and the data mining algorithms wereapplied to student achievement of English. This article’s data comes from a collegeclass’s45primary entrance simulation results. The class’s student achievementthroughout the school were more representative, the results can pull grade, andvarious kinds of questions can also pull-grade scores that proposed method isapplicable.This paper established the following two models.The first model is a rough set attribute model, and this model is applied to theEnglish results, and it studied the importance of the English exam’s various kinds ofquestions. Through the establishment of rough set attribute model to analyze whatkinds of questions to the greatest degree of change in the decision-making properties and classification, and determined what conditions the most important attribute. Afterremoving a property from discrete data after the calculated what changes will occurclassification decisions, it analyzed the importance of the condition attribute. Studingthe effects of various kinds of questions to learn English and comparing the results ofthis factor analysis and the results, it provided a reference for the various kinds ofquestions the importance of English studies.From the result of rough set attribute model point of view, in the all kinds ofquestions in the college entrance examination in English, reading comprehensionscores’ reference is largest, followed by hearing, cloze and writing, and the minimalimpact on the achievement of English questions were vocabulary individual fill in theblank and essay Correction.By comparing the two methods that rough set attribute model and factorsanalysis, it can be found that consistent with the results obtained in rough set attributemodel were equal to factor analysis results. So it verified the correctness of rough setattribute model.The second model, using the concept of upper approximation set and lowerapproximation set, rough set and K-means clustering algorithm are combined to createa rough clustering model, and this model is applied to student achievement in English,according to the results of cluster analysis, it can distinguish the different studentswho learning English provided a different approach.Through the establishment of two different models, combining with the currentsituation of education, it can propose different method of learning English andrecommendations to different students.