Data Analysis of Undergraduate Employment Based on Decision Classification Algorithm

Abstract

When the school uses the employment situation analysis system to analyze the employment situation of undergraduate students every year, because the classification decision rules are complex, it is difficult for the system to understand the complex rules when analyzing the employment situation of graduates, which leads to the slow operation of the system. Therefore, a brand-new employment situation analysis system is designed based on the decision classification algorithm. On the system hardware, the communication circuit of CAN bus is redesigned. On the software side, we use the decision classification algorithm to set up a most concise system classification decision rule, so as to automatically generate the analysis results of the employment situation of undergraduate graduates. The proposed system is applied to the analysis of the employment situation of undergraduate graduates in a university. The results show that the time taken by the system to analyze the employment situation is 97 356 ms and 70 372 ms shorter than the previous system. It can be seen that the rules set this time are easier to be understood by the system, and the results of employment situation analysis can be quickly obtained.