dc.creatorPeralta Márquez, Billy
dc.creatorPoblete, T.
dc.creatorCaro Saldivia, Luis
dc.creatorIEEE
dc.date2016
dc.date2021-04-30T16:30:29Z
dc.date2021-04-30T16:30:29Z
dc.date.accessioned2021-06-14T22:03:47Z
dc.date.available2021-06-14T22:03:47Z
dc.identifierPROCEEDINGS OF THE 2016 35TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC),Vol.,,2016
dc.identifierhttp://repositoriodigital.uct.cl/handle/10925/2792
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3299657
dc.descriptionThe 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.
dc.languagees
dc.publisherIEEE
dc.sourcePROCEEDINGS OF THE 2016 35TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC)
dc.subjectfeature selection
dc.subjectdecision trees
dc.subjecteducation
dc.titleAutomatic Feature Selection for Desertion and Graduation Prediction: A Chilean Case
dc.typeMeeting


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