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  • 标题:Uma abordagem para predição de estudantes em risco utilizando algoritmos genéticos e mineração de dados: um estudo de caso com dados de um curso técnico a distância
  • 本地全文:下载
  • 作者:Emanuel Queiroga ; Cristian Cechinel ; Marilton Aguiar
  • 期刊名称:Anais dos Workshops do Congresso Brasileiro de Informática na Educação
  • 印刷版ISSN:2316-8889
  • 出版年度:2019
  • 卷号:8
  • 期号:1
  • 页码:119-128
  • DOI:10.5753/cbie.wcbie.2019.119
  • 出版社:Anais dos Workshops do Congresso Brasileiro de Informática na Educação
  • 摘要:This paper demonstrates a non-traditional approach attempting to predict student dropout. For this, evolutionary system technics are used, which in this implementation seeks the optimization through the competition of six classifiers with initially random generated parameters among the possible ones for each classifier, the fitness function ranks the population at the end of each epoch. At last, the fittest individuals of each classifier are selected, and they compete with each other. The six classifiers, using the standard configuration, are compared and then contrasted with those obtained by the proposal. In this way, it was possible to obtain an improvement in the performance, with average gains ranging from 4% to 6%, in some cases up to 10%, depending on the metric.
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