Analysis Of Student Achievement Based On Data Mining

The contents of this paper are from student achievement over the years, and related databases to find the rules we are interested in. School can adjust the teaching content and teaching methods can be improved to adapt to student learning and to improve teaching quality.This paper introduces the research background and development status at home and abroad, and by introducing the basic knowledge of database and data mining knowledge as the theoretical basis of this study to analyze student achievement. In the performance analysis process, according to the actual application needs, firstly it introduces the data pre-processing of the relevant knowledge, and the theoretical basis of this knowledge to the data will be collected in form of favorable data mining stored in the database to be excavated. Then introduces the classic data mining algorithms, which is focused on APRIORI algorithm. And in order to make up for lack of APRIORI algorithm, The paper introduces of FP growth algorithm. Light of the actual system development needs, the FP algorithm corresponding adjustments and improvements to the FP tree growth, especially after change, it is more conducive to data storage and frequent pattern can be found easily. Finally, according to association rules, the system deletes misleading rules.For the final development of the system, in addition to simple data analysis, the main goal is to discover association rules and association rules of interest will be displayed in front of users in the form of easy to understand. The system requires simple input, intuitive operation, also less overhead.