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基于贝叶斯网络模型的学生成绩预测研究

发表时间:2018-01-15  浏览量:650  下载量:77
全部作者: 张素花,谭子健,周静静,赵东方
作者单位: 华中师范大学数学与统计学学院
摘 要: 首先,根据主成分分析法对数据进行筛选,得到影响学生学业成绩的主要因素;其次,根据贝叶斯统计理论建立贝叶斯预测模型,并利用五年级部分数据作为训练数据,从而对五年级6班学生的学业成绩进行预测;最后,对预测结果进行分析。预测结果中学生学业成绩的等级与实际成绩等级比较吻合,表明用贝叶斯模型预测学生的学业成绩是可行的。该研究结果可为教师和家长提供一些建设性建议。
关 键 词: 数理统计学;成绩预测;贝叶斯网络模型;主成分分析;Matlab程序
Title: Prediction of students’ performance based on Bayesian network model
Author: ZHANG Suhua, TAN Zijian, ZHOU Jingjing, ZHAO Dongfang
Organization: School of Mathematics and Statistics, Central China Normal University
Abstract: Firstly, according to the method of principal component analysis, the main factors that affect students’ academic performance are selected. Secondly, the Bayesian prediction model is established according to Bayesian statistical theory, and some data from grade 5 are used as training data, then the students’ academic performance prediction of class 6, grade 5 is achieved. Finally, the forecast results are analyzed. The student’s academic performance in forecast grade and in actual grade are coincided. The results show that the Bayesian prediction model is feasible for the prediction of student’s academic performance and provides some constructive suggestions for the education of teachers and parents.
Key words: mathematical statistics; performance prediction; Bayesian network model; principal component analysis; Matlab program
发表期数: 2018年1月第1期
引用格式: 张素花,谭子健,周静静,等. 基于贝叶斯网络模型的学生成绩预测研究[J]. 中国科技论文在线精品论文,2018,11(1):28-32.
 
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