摘要
决策树是归纳学习和数据挖掘的重要方法,通常用来形成分类器和预测模型。对课程知识点个性化教学中的大量数据,运用数据挖掘算法中的决策树C4.5算法对所给数据进行处理,选取决策属性,构造决策树,提取分类规则,获取每一个知识点与不同类型的学生个性化教学的关系。在Clementine中的试验结果表明,该算法能够将数据准确分类和预测,得到有价值的结论,供教师决策分析。
Decision tree is an important method in indeuction as well as in data mining,which can be used to build classification and predictive model.For number of data of the personalized teaching in knowledge points of course,C4.5 data mining algorithm is used to solve the selected data,choose decision-making attribute,build a decision tree and extract the classify rules,it can acquire the relationship between each of knowledge point and personalized teaching in different types of students.Experimental results show that it can classify and predict data accuracy and find some valuable results and provide decision-making and analysis for teachers.
出处
《长江大学学报（自科版）（上旬）》
CAS
2010年第3期296-299,共4页
JOURNAL OF YANGTZE UNIVERSITY (NATURAL SCIENCE EDITION) SCI ＆ ENG
基金
2008年度广东远程开放教育科研基金项目(KY0809)
