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Identificação dos Fatores que Influenciam a Evasão em Cursos de Graduação Através de Sistemas Baseados em Mineração de Dados: Uma Abordagem Quantitativa

Laci Mary Barbosa ManhãesSérgio Manuel Serra da CruzRaimundo J. Macário CostaJorge ZavaletaGeraldo Zimbrão

This paper uses data mining techniques to indentify key variables related with students failures in completing their undergraduate studies. In our approach, classification analysis is used to manipulate academic data of students of the largest Brazilian Federal University. Differently from other works, our research shows that even analyzing three different classes of students it was possible to have a global precision above 80%. The Naïve Bayes model was used to visualize the key variables used to separate the distinct classes of students.

http://www.lbd.dcc.ufmg.br/colecoes/sbsi/2012/0046.pdf

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