Automatic Feature Selection for Desertion and Graduation Prediction: A Chilean Case

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dc.contributor.authorPeralta Márquez, Billy
dc.contributor.authorPoblete, T.
dc.contributor.authorCaro Saldivia, Luis
dc.contributor.authorIEEE
dc.date2016
dc.date.accessioned2021-04-30T16:30:29Z
dc.date.available2021-04-30T16:30:29Z
dc.description.abstractThe 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.identifier.citationPROCEEDINGS OF THE 2016 35TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC),Vol.,,2016
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/2792
dc.language.isoes
dc.publisherIEEE
dc.sourcePROCEEDINGS OF THE 2016 35TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC)
dc.subject.englishfeature selection
dc.subject.englishdecision trees
dc.subject.englisheducation
dc.titleAutomatic Feature Selection for Desertion and Graduation Prediction: A Chilean Case
dc.typeMeeting
uct.catalogadorWOS
uct.indizacionISTP
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