Abstract
In order to explore the relevant mechanisms of graduate students obtaining scholarships and employment, this study starts from the perspective of data science and utilizes the C5.0 algorithm to collect 9 basic attributes of students, thereby determining the input variables of the decision tree. Employment is taken as the output variable. The employment situation of the graduates in 2021 is used as the training set, and the situation of the graduates in 2022 is used as the test set. This opens the black box of the mechanism of scholarship acquisition and student employment. The study indicates that the publication of papers, whether a student cadre, and academic conference papers are the three most critical indicators for employment
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