Title :
Data mining techniques for predicting student performance
Author :
K. P. Shaleena;Shaiju Paul
Author_Institution :
Dept. of Computer Science &
fDate :
3/1/2015 12:00:00 AM
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"
Conference_Titel :
Engineering and Technology (ICETECH), 2015 IEEE International Conference on
DOI :
10.1109/ICETECH.2015.7275025