摘要
教师对学生成绩分析一般仅统计处在优、一般、差的人数,对每位学生具体擅长与不擅长的课程往往无法了解。为了能挖掘出每位学生擅长与不擅长课程,更好地提高教学质量,利用Python语言开发了基于数据挖掘的学生成绩分析系统。使用决策树算法中的CART算法对学生成绩进行分析预测,对决策树进行剪枝降低树的高度防止过拟合,不断优化决策树模型,使分析预测达到一个较为精准的水平,更好地为高校教学服务。
The analysis and processing of students’performance by teachers is only to count the number of students whose performance is in the excellent,general and poor grades.It is often impossible to understand the specific courses that each student is good at or not good at.If the teacher can find out each student’s good at the curriculum and not good at the curriculum,it will play a positive role in improving the quality of teaching.The student achievement analysis system based on data mining is developed by using Python language.The system uses CART algorithm in decision tree algorithm to analyze and predict the student’s performance,prunes the decision tree to reduce the height of the tree to prevent over fitting,and constantly adjusts parameters to optimize the decision tree model,so that the analysis and prediction can reach a more accurate level and provide better service for college teaching.
作者
李小白
黄洪标
陈鑫
杜平
LI Xiaobai;HUANG Hongbiao;CHEN Xin;DU Ping(Guangdong Construction Polytechnic,Guangzhou 511500,China)
出处
《现代信息科技》
2020年第16期82-84,共3页
Modern Information Technology
关键词
数据挖掘
决策树算法
成绩分析系统
data mining
decision tree algorithm
achievement analysis system
