Score Analysis System Of Optional Courses Through The Research Of Data Mining

The technology of Data Mining is effective means for abstracting useful information from the vast data. It provides a convenient way for obtaining the interesting and useful information from a vast amount of data to people.Data Mining has been comparatively less applied in education. Schools have accumulated a wealth of teaching and administrating data which haven't been effectively made use of. They are like a treasure house to be exploited. The data application of students'information and results remains a low level of simple preparation and inquiry. In recent years, the increasing number of students has brought great trouble in teaching and administrating. Therefore, traditional teaching and administrating methods can't be suitable for the social development.The article expounds the process, task, method and technique of Data Mining and deeply studies Apriori algorithms of arithmetic of association rule and ID3 algorithms of arithmetic of classification. It introduces the accomplished Data Mining process of Apriori and ID3 algorithms according to the optional courses online of Qingdao Electronics School.The Chapter One expounds the background and current situation of Data Mining, raises the basis of the selection and analyzes the practical use of the study of researching this topic.The first half of Chapter Two presents the speculative knowledge about Data Mining from the concept,the process,the task,the classification,the staple technology and the methods. The second half probes the speculative knowledge of definite arithmetic of Data Mining from the algorithms of ID3 decision tree and the relating rules of Apriori. It emphasizes the algorithms of ID3 decision tree, analyzes how to adopt informationism and how to prune the decision tree in the measure of attribute selection. Then it extracts the relating rules from the example of the problem in students'shopping, which introduces the important concept of support level and confidence level. It also expounds Apriori algorithms.Chapter Three put emphasis on Data Mining in the design and achievement of students'marks analytic system. According to the given proposal, a lot of work need to be done during the stage of data preprocessing. The paper designed two data mining models, which integrally achieves the overall process of data classification mining. The arithmetic of ID3 decision tree makes use of postmortem pruning, which can form decision tree to analyze the factors influencing the students' marks and produce the principle of classification. Apriori association rule algorithms sum up the relating rules of interaction between courses, so we can find the disciplines and feedback them to the teaching.Chapter Four emphasizes the decision tree classification system developed by applying the Data Mining classification technique. The has the functions of interviewing data files, generating decision tree, pruning decision tree, producing classification rules and predicting the new data.Chapter Five emphasizes the ways to use Apriori association rule algorithm to evaluate and teach the students to mine. Through some operations of fixing mining objects, preparing the data, data mining, interpretation of result and knowledge assimilation, we can analyze the process of mining, obtain the rule conclusion and sum up the elements that can influence the quality of teaching.Through effective data mining, people can obtain a lot of unexpected knowledge and thus will promote the further improvement of the quality of teaching and scientifically guide teaching. The study of this paper gives good suggestions to practical teaching management, adds new contents to the teaching management of the school and opens the situation of network training. With the further development of data mining, it will be applied to teaching more and more and bring unprecedented gains and surprises.