Application Research of College Student Employment Prediction Model Based on Decision Tree Algorithm

Employment is the cornerstone of people's livelihoods and plays a crucial role in economic development. In recent years, the scale of university enrollment has been continuously expanding, leading to a growing population of university graduates. In 2022, the total number of university graduates reached a historic high of 10.76 million, and the employment pressure on graduates has increased significantly, exacerbated by the impact of the COVID-19 pandemic. Therefore, it is of practical significance to apply effective analysis and prediction methods to understand employment trends. This article, based on the decision tree algorithm, establishes an employment prediction model using data related to university students' employment and academic performance, aiming to uncover key factors influencing student employment. The F-value of the employment prediction model constructed using the decision tree algorithm is 0.9026, indicating that the model performs well in predicting the employment status of university students. The results demonstrate that this model can accurately predict students' employment outcomes and identify influential factors including gender, ethnicity, graduation time, and academic performance.