Analysis Of Students' Employment Data Based On Decision Tree Algorithm And Association Rule Analysis Method

It is the focus of the society to improve the employment rate of the school and the quality of students’ employment. The traditional students’employment information is just used by simple store and query. In order to use students’employment information efficiently and find out the inlaying laws to guide the future education, the paper focuses on the mining of the students’ employment. This paper is divided into six parts.The first part is the introduction part. It mainly introduces the hot research fields and key problems of the data mining technology, and the research progress at home and abroad.The second part introduces the algorithms. It mainly introduces the main technologies and the algorithms for the data mining such as decision data algorithm, association rule algorithm and Bayesian algorithm. For these algorithms, it expounds their implementation through examples. It analyzes the advantages and disadvantages of three kinds of algorithms in detail and relates the application range.The third part mainly introduces the decision tree algorithm based on association rules. This algorithm includes preprocessing, association rules, decision tree analysis and processing, and integrated analysis and processing, and so on. Preprocessing mainly involves the integration, extension and discretization of data to transfer all kind of data into binary numbers to be convenient for the following algorithm processing. For the association rules, we divide the enterprise properties into several layers, and analyze the resulting association rules. By the decision tree algorithm we build association rules to mine the hidden relationships between students and enterprise attribute.The fourth part mainly constructs the students’employment information data model. It talks about the data collection and data modeling in detail.The fifth part verifies the reliability of the algorithm by dealing a group of students’ employment information with decision tree algorithm based on association rules.The sixth part makes a summary for this paper, and then makes the plan for the future work.The decision tree analysis method based on association rules can excavate the hidden information in students’ employment data; it has great help to improve the education for schools and the plan for students themselves. The algorithm works with high efficiency, be robust, also has positive effect for other types of data mining.