Data mining
Data mining
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DOI：
10.4135/9781452244723.n136
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发表时间：
1996
期刊：
影响因子：
--
通讯作者：
P. Adriaans;Dolf Zantinge
中科院分区：
文献类型：
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作者：
P. Adriaans;Dolf Zantinge
摘要学生根据指定时间完成研究的能力是评估大学认证的重要因素。良好的认证显示了大学的形象。出现的问题是，许多学生错过了学习的完成，这阻碍了他们的学习计划的认证。这项研究的目的是设计一个可以支持与学生毕业有关的决策的申请计划。这项研究应用了中殿贝叶斯方法，该方法可以根据计算机科学学院和信息系统研究计划的Alashalia Mander过去经验来预测未来的机会。这项研究是使用Nave Bayes方法进行学生毕业分类的数据挖掘申请计划，该计划有望帮助教育工作者按时完成研究，并发展他们在研究计划中提高认证的能力。设计成功。
Abstract A student's ability to complete a study according to a designated time is an important factor in assessing university accreditation. A good accreditation shows the image of a university. The problem that arises is that many students miss the completion of their studies, which hinders the certification of their learning programs. The purpose of this study is to design an application program that can support student graduation-related decisions. This study applies the Nave Bayesian method, which can predict future opportunities based on past experience at the University of Al- Ashalia Mander, School of Computer Science, and Information Systems Research Program. This study is a data mining application program for student graduation classification using the Nave Bayes method, which is expected to help educators complete their studies on time and develop their ability to increase accreditation in their research programs. The design was successful.