机器学习在数学成绩预测中的应用研究

学生的成绩是教师优化教学过程、调整教学决策的重要标准,文章运用了多种机器学习算法对学生的数学成绩进行建模,通过比较模型的准确率、精确率、召回率、F1-Score,最终确定了人工神经网络是最优的模型。通过对数据特征重要性评估,得出了影响学生成绩的主要因素是母亲的工作、父亲的工作、出勤量、挂科数、健康状况、出去玩的频率及周饮酒量的结论。

Research on the Application of Machine Learning in Mathematics Achievement Prediction

Students'performance is an important standard for teachers to optimize teaching process and adjust teaching decision-making.In this paper,a variety of machine learning algorithms are used to model students'mathematical performance.By comparing the accuracy,accuracy,recall rate and F1 score of the model,it is finally determined that the artificial neural network is the optimal model.Through the evaluation of the importance of data characteristics,the main factors affecting students'performance are mother's work,father's work,attendance,number of subjects,health status,frequency of going out to play and weekly alcohol consumption.