The Application Of Decision Tree In The Students' Result Analysis

With the development of database technology as well as the widespread application of database management system, the capability of collecting data was improved rapidly, and lots of data have been accumulated. There was a large amount of valuable information hiding behind these data. In order to analyze these data in a higher level and obtain the latent information to instruct work and life, the Data Mining technology is brought forward. The Data Mining is a procedure of distilling available information and knowledge from mass, incomplete and random data. The Data Mining had been applied and studied in these years, and it has been applied in many domains successfully, such as business, finance and medical treatment. However, little is applied in teaching.Because of the sharp increase of the enrolled students'number, there are lots of problems which can influence the quality of teaching in the universities. For the purpose of providing reliable suggestions for teachers, this dissertation, taking the author's university for example, puts forward a research project of scooping out the valuable information behind the students'results by using the Decision Tree.The Decision Tree technology, which is the main technology of the Data Mining classification and forecast, is the classifying rule that infers the Decision Tree manifestation through group of out-of-orders, the non-rule examples. The Decision Tree exceeds the others in the feature of well understanding, well training and achievable. Therefore, the Decision Tree technology was used in research of student result analysis.Based on the research background of the Data Mining, the Decision Tree was applied to result analysis for the purpose of improving the teaching quality. This dissertation has finished the following works: 1. The research and discussing of the basic knowledge of Data Mining. Based on the introduction of elementary concept of Data Mining, the objection and findable mode are classified and concluded detailedly. In addition, some regular Data Mining technology is analyzed.2. The technology of Decision Tree is discussed detailedly. In the third chapter, the concrete steps of excavating data are analyzed. And the main arithmetic and basic ideas of Decision Tree are discussed and concluded detailedly. In addition, the difference between each arithmetic has been compared objectively.3. The shortcomings of the present students'result analysis are pointed out. In view of the importance and function of the students'result analysis, the vital significance of applying the Data Mining in the analysis is proposed.4. The entire procedure of the Decision Tree technology excavating the students'result analysis has been completely introduced. The fifth chapter is the core of this thesis. Use the examination table and such other ways to collect and pretreat data; The C4.5 arithmetic was used to generate a Decision Tree, and consequently the classification rule was obtained.