摘要
基于挖掘分析影响学生学习效果主因素为目的,采用了能够对数据进行挖掘分析并直观展示结果的决策树技术方法,通过某班学生某门课程的学习信息数据进行挖掘分析的试验,采用ID3和C4.5算法生成决策树,并使用后剪枝技术精简决策树,最终找出决定本门课程学习效果的主要因素-考勤。从而为分析学生学习情况,给予个性化提示与指导提供有效的建议。
Based on the analysis of the main factors that influence the students＇ learning effect, the method of decision tree is adopted to analyze the data and display the resuhs directly. Through the study of a certain class of students learning data mining analysis of the test,it uses the ID3 and C4.5 algorithm to generate a decision tree and streamline it with post-pruning technology. Finally the main factors influenced the effectiveness of this course, checking work attendance was found out. Then an effective suggestions on individualized presentation and guidance was provided after analysis of students learning.
作者
韩丽娜
韩改宁
HAN Li-na HAN Gai-ning(Institute of Graphics and Image Processing, Xian Yang Normal College, Xianyang 712000, China)
出处
《电子设计工程》
2017年第2期18-21,共4页
Electronic Design Engineering
基金
陕西省教育厅资助项目(14JK1802)
咸阳师范学院引进人才项目(13XSYK053)
陕西省教育科学"十二五"规划2014年度项目(SGH140802)
关键词
决策树
信息熵
信息增益
信息增益率
decision tree
information entropy
information gain
information gain rate
