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Embedding Na?ve Bayes Algorithm Data Model in Predicting Student Graduation

Ace C.LagmanJoseph Q.CallejaMa.Corazon G.FernandoJoseph G.GonzalesJohn Benedict LegaspiJohn Heland Jasper C.OrtegaRonel F.RamosMaria Vicky S.SolomoRegina C.Santos

FEU Institute of Technology

摘要:In the Philippines,according to Philippine Authority of Statistics,there is an imbalance between the student enrollment and student graduation.Almost half of the first-time freshmen full time students who began seeking a bachelor’s degree do not graduate on time.The study aims to utilize how Na?ve Bayes algorithm-a data classification algorithm that is based on probabilistic analysis-can be used in educational data mining specifically in student graduation.The study is focused on the application of the Na?ve Bayes algorithm in predicting student graduation by generating a model that could early predict and identify students who are prone of not having graduation on time,so proper remediation and retention policies can be formulated and implemented by institutions.
会议名称:

2019 the 3rd International Conference on Telecommunications and Communication Engineering (ICTCE 2019)

会议时间:

2019-11-09

会议地点:

日本东京

  • 专辑:

    教育与社会科学综合; 电子技术及信息科学

  • 专题:

    教育理论与教育管理; 计算机软件及计算机应用; 计算机软件及计算机应用

  • DOI:

    10.26914/c.cnkihy.2019.066805

  • 分类号:

    G434;TP311.13

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页码:52-57 页数:6 大小:440k

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