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The national high school exam (Enem) is a test required by most Brazilian universities to select students. In this exam, several characteristics about the candidates are collected. Some of these characteristics do not contribute significantly to the performance prediction, thus representing an excessively large dataset, requiring exponential computational resources to identify them. To solve this problem, this work applies algorithms for the selection and classification of attributes, identifying twenty main characteristics that contribute to the high or low performance of students in this exam, in the last twenty-two years (1998-2019).

Usando Mineração de Dados para Identificar Fatores mais Importantes do Enem dos Últimos 22 Anos