Research on the Investment Return of Study Abroad Based on Machine Learning
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Sending family teens to study abroad has become an educational option for middle-class families in China's big cities. Due to the high economic cost and time cost of studying abroad, it is necessary to analyze the human resources investment to provide the family with a basis for decision-making on whether to make this investment. This paper proposes a method for calculating the return on investment in studying abroad based on the GBDT model. By selecting multiple micro variables and macro variables as input, the ResNet-GBDT regression model is used to predict the annual salary of students in different regions and industries after graduation and estimate the actual situation of studying abroad. The experimental results show that the model can predict the actual return of study abroad in different regions to a certain extent.
study abroad; human resources investment; return on investment; micro and macro variables