大学生创新能力预测模型的构建与应用研究

Research on the Construction and Application of the Innovation Ability Predicting Model of College Students

为了构建基于机器学习算法的大学生创新能力预测模型,实现对创新能力的评价和预测,通过收集大学生在课程学习、学科竞赛、论文发表和实践创新等多方面的数据,结合随机森林算法进行集成学习,综合考虑多维度数据并提取关键特征,形成了创新能力分类评价和预测模型。经过训练,该模型展现出良好的预测性能,实验结果表明其具有较高的准确性和稳定性。不仅为大学生创新能力的评价和预测提供了新的思路和方法,还有助于推动创新能力培养工作的深入发展,为高校教育创新提供有力支持。

In order to construct a prediction model for college students’innovation ability based on machine learning algorithms,and to evaluate and predict their innovation ability,data from various aspects such as course learning,subject competitions,paper publishing,and practical innovation are collected,and combined with the random forest algorithm for ensemble learning,a classification evaluation and prediction model for innovation ability is formed by comprehensively considering multidimensional data and extracting key features.After training,the model demonstrates good predictive performance,and experimental results show that it has high accuracy and stability.It not only provides new ideas and methods for evaluating and predicting the innovation ability of college students,but also helps to promote the in-depth development of innovation ability training and provides strong support for innovation in higher education.