高校学生全画像学业成绩预警模型分析

Analysis of a full picture academic performance warning model for college students

基于CatBoost算法,利用高校学生的全面画像数据,建立了学业成绩预警模型,可有效预防学生学业成绩的严重下滑。文章以江苏连云港一所高校的学生学业成绩数据为对象,采用机器学习算法CatBoost,并以学生的历史学业成绩数据为基础进行学业成绩的预测,其准确率达到了79.6%。

Based on the CatBoost algorithm and utilizing comprehensive profile data of college students,a performance warning model was established,which can effectively prevent a serious decline in student academic performance.The article takes the academic performance data of students from a university in Lianyungang,Jiangsu as the object,uses the machine learning algorithm CatBoost,and predicts academic performance based on historical academic performance data of students,with an accuracy rate of 79.6%.