A Case Study of Applying the Classification Task for Students' Performance Prediction

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dc.contributor.authorGuerra, M. S.
dc.contributor.authorAsseiss Neto, H.
dc.contributor.authorOliveira, S. A. [UNESP]
dc.contributor.institutionInst Fed Mato Grosso Do Sul
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-11-26T15:47:29Z
dc.date.available2018-11-26T15:47:29Z
dc.date.issued2018-01-01
dc.description.abstractThis paper presents a study involving the application of data mining techniques for extracting knowledge from the academic database of the Federal Institute of Mato Grosso do Sul (IFMS). The main goal is the prediction of students' performance on specific classes of the Internet Systems course. Extra students' information such as age and gender are also considered. Knowledge Discovery in Databases (KDD) is described and its steps are applied in this study. The classification task is used to generate decision trees that are tested on different datasets. The results show a success rate of 75.8% on the classification of new and unknown students based on the decision trees models generated.en
dc.description.affiliationInst Fed Mato Grosso Do Sul, Tres Lagoas, MS, Brazil
dc.description.affiliationUniv Estadual Paulista, Ilha Solteira, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Ilha Solteira, SP, Brazil
dc.format.extent172-177
dc.identifier.citationIeee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 1, p. 172-177, 2018.
dc.identifier.fileWOS000425326100026.pdf
dc.identifier.issn1548-0992
dc.identifier.urihttp://hdl.handle.net/11449/160101
dc.identifier.wosWOS:000425326100026
dc.language.isopor
dc.publisherIeee-inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Latin America Transactions
dc.relation.ispartofsjr0,253
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectdata mining
dc.subjectclassification task
dc.subjectacademic database
dc.titleA Case Study of Applying the Classification Task for Students' Performance Predictionen
dc.typeArtigo
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee-inst Electrical Electronics Engineers Inc

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