@inproceedings{4398e1424d2f4b99904ee90c768ea766,
title = "Automatic feature selection for desertion and graduation prediction: A chilean case",
abstract = "The high rate of university dropout and low graduation rates are very relevant social problems today. Since there are many possible causes of desertion and university graduation, in this paper, we propose to find, analyze and weigh the factors that allow predicting if a student will drop out or graduate according to prior information available using data mining techniques and statistical models. We will focus in the case of Catholic University of Temuco, using real data from that institution. This study reveals relevant variables in opinion of human experts, which demonstrates the ability of automatic models to represent the dropout and graduation at the university.",
keywords = "decision trees, education, feature selection",
author = "B. Peralta and T. Poblete and L. Caro",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 35th International Conference of the Chilean Computer Science Society, SCCC 2016 ; Conference date: 10-10-2016 Through 14-10-2016",
year = "2017",
month = jan,
day = "27",
doi = "10.1109/SCCC.2016.7836055",
language = "English",
series = "Proceedings - International Conference of the Chilean Computer Science Society, SCCC",
publisher = "IEEE Computer Society",
booktitle = "Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016",
address = "United States",
}