首页|基于数据挖掘的高校学生考研成绩预测分析

基于数据挖掘的高校学生考研成绩预测分析

Research on Prediction and Analysis of College Students'Postgraduate Entrance Examination Results Based on Data Mining

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  • 维普
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随着硕士研究生考试初试难度越来越大,影响考研结果的因素众多,以安徽建筑大学建筑类设计专业高校学生为研究对象,以本科毕业生的在校成绩和考研初试成绩作为样本数据,通过Logistic回归分类算法、SVM支持向量机算法、KNN算法三种实验建模测试对比,寻找对应变化规律,提高考研初试成绩变量之间的关联性,从而得出预测结果,从平均预测误差看,Logistic回归分类算法的预测方法具有较高的适应力和稳定性,准确性更适合初试无高数科目的建筑类设计专业高校学生.得出要特别注重加强对专业课、课程设计的学习,同时对政治和英语注意学习态度的结论.为帮助其预测学业发展趋势、制定职业生涯规划上提供数据支撑.
With increasing difficulty on preliminary test of postgraduate entrance examination as well as numbers of factors affecting results of the examination,taking college students majoring in architectural design of Anhui University of architecture as the research ob-ject,this study uses grades at school and the preliminary test grades of the undergraduate graduates as the sample data,through the com-parison of three experimental modeling tests of Logistic regression classification algorithm,SVM algorithm and KNN algorithm,to find cor-responding change rules and improve the correlation between score variables from preliminary tests of postgraduate entrance examination,so as to obtain the prediction results.From the perspective of average prediction error,the prediction method of logistic regression classifi-cation algorithm has high adaptability and stability,and the accuracy is more suitable for college students majoring in architectural design without higher mathematics in preliminary tests.It is concluded that special attention should be paid to strengthening the study of special-ized courses and curriculum design,while paying attention to the learning attitude towards politics and English.The conclusion helps them predict their academic development trend and provides data support for career planning.

prediction of postgraduate entrance examination resultslogistic algorithmSVM algorithmKNN algorithmarchitecture students

王昊禾、张悦、江宇琪

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安徽建筑大学 建筑与规划学院,安徽 合肥 230601

合肥工业大学 管理学院,安徽 合肥 230009

滁州学院 美术与设计学院,安徽 滁州 239000

安徽建筑大学 学生处,安徽 合肥 230601

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考研初试成绩预测 Logistic算法 SVM算法 KNN算法 建筑类学生

安徽省2020年弘扬社会主义核心价值观名师工作室项目"悦己兮"网络思政育人工作室项目安徽高校人文社会科学研究项目

sztsjh-2020-1-50sztsjh-2020-1-40SK2020JD03

2024

武夷学院学报
武夷学院

武夷学院学报

影响因子：0.28
ISSN：1674-2109
年,卷(期)：2024.43(1)
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