Data Mining Techniques for Predicting Student Performance

被引：0
|
作者：
Shaleena, K. P. [1 ]
Paul, Shaiju [1 ]
机构：
[1] Jyothi Engn Coll, Dept Comp Sci & Engn, Trichur, Kerala, India
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON ENGINEERING AND TECHNOLOGY (ICETECH) | 2015年
关键词：
educational datamining; classification; prediction; decision trees; class imbalance; cost sensitive classification;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Predicting student performances in order to prevent or take precautions against student failures or dropouts is very significant these days. Student failure and dropout is a major problem nowadays. There can be many factors influencing student dropouts. Data mining can be used as an effective method to identify and predict these dropouts. In this paper, a classification method for prediction is been discussed. Decision tree classifiers are used here and methods for solving the class imbalance problem is also discussed.
引用
收藏
页码：48 / 50
页数：3
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