基于机器学习的研究生创新创业教育影响因素分析

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中图分类号：G643 文献标识码：A D0I：10.7535/j.issn.1671-1653.2026.01.011

Abstract： Graduate innovation and entrepreneurship education is a vital pathway for cultivating innovative talents. Research findings indicate that the current development of graduate innovation and entrepreneurship education exhibits diferentiated characteristics compared to undergraduate education，reflecting the optimized allocation of educational resources for different student groups. However， there still exist a series of pressing practical challenges and issues to be addressed， including the need for a systematic optimization of the evaluation system，a lack of targeted guidance， and an incomplete construction of practical platforms for innovation and entrepreneurship education. By applying PAM clustering analysis and the random forest algorithm，key influencing factors such as classroom participation， social practice engagement， research outputs，competition performance，and the availability of innovation and entrepreneurship education facilities are identified.Based on bothissue-specific analysis and empirical findings from machine learning， targeted recommendations are proposed accordingly.

Keywords： innovation and entrepreneurship education； graduate education； machine learning

一、引言

党的二十大报告深刻阐明教育、科技、人才是现代化建设的三大战略支点，强调要以自主创新为引领，加速推进创新驱动发展战略实施。（剩余8195字）