基于Adaptive-Lasso的本科成绩统计分析

The Statisitical Analysis of Undergraduate Grades Based on the Adaptive-Lasso

  • 摘要: 本文主要研究了合肥工业大学数学学院数学专业学生的本科成绩状况, 应用多元线性统计方法, 探讨了前期所有课程成绩对后期成绩的影响. 首先对前期课程进行主成分分析, 并采用逐步回归方法建立了后期成绩与主成分之间的回归模型. 其次, 采用Adaptive-Lasso方法建立后期成绩与前期课程成绩间的Adaptive-Lasso回归模型. 最后, 对以上模型进行对比分析. 研究表明, 基于~Adaptive-Lasso方法的主成分回归模型能很好地拟合后期成绩, 并对后期成绩情况给出合理的解释.

     

    Abstract: In this paper, the multivariate linear statistical method is applied to research the undergraduate grades of students from the school of mathematics in Hefei University of Technology, and explore the impact on the later achievement by the early stage of achievement from all undergraduate courses. First, we get the main components from the previous courses by principal component analysis, then construct a linear regression model between the later achievement and main components by the stepwise regression method. Next, a linear regression model between the later achievement and the early stage of achievement from all undergraduate courses is constructed by Adaptive-Lasso method. Finally, comparative analysis is performed for the result of the above models. The research shows that the principal component regression model based on the Adaptive-Lasso method can well fit the later achievement, and give a reasonable explanation for the later academic performance.

     

/

返回文章
返回