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