Extracting Indicators Model for the Development of Undergraduates in Guangdong Province Based on Machine Learning Algorithms

Abstract

The aim is to use machine learning methods to select indicators of undergraduates' development. This paper adopts questionnaire survey. Then, we collected nearly 3000 pieces of data through 2 months and used the lasso regression model (LASSO), ridge regression model (RRM) and partial least squares regression model (PLSRM) of machine learning to select more relevant indicators among 15 indicators. According to the results, these indicators are main indicator of the development of undergraduate, included score, business project, paper, patent, competitions in academic, honor, public service, the level of English and professional qualification certificate. It can not only lay the foundation for the subsequent research but also help mentor to guide them in the right way.