DocumentCode :
3659083
Title :
Data mining techniques for predicting student performance
Author :
K. P. Shaleena;Shaiju Paul
Author_Institution :
Dept. of Computer Science &
fYear :
2015
fDate :
3/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
3
Abstract :
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.
Keywords :
"Data mining","Classification algorithms","Decision trees","Prediction algorithms","Accuracy","Conferences","Data preprocessing"
Publisher :
ieee
Conference_Titel :
Engineering and Technology (ICETECH), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICETECH.2015.7275025
Filename :
7275025
Link To Document :
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