Academic Data Mining was one of emerging field which comprise procedure of examined students details by different elements such as earlier semester marks, attendance, assignment, discussion, lab work were of used to improved bachelor academic performance of students, and overcome difficulties of low ranks of bachelor students. It was extracted useful knowledge from bachelor academic students data collected from department of Computing. Subsequently preprocessing data, which was applied data mining techniques to discover classification and clustering. In this study, classification method was described which was based on naive byes algorithm and used for Academic data mining. It was supportive to students along with to lecturers for evaluation of academic performance. It was cautionary method for students to progress their performance of study.
翻译:学术数据开采是一个新兴领域,它包括了通过不同要素,例如学前学期成绩、出勤、分配、讨论、实验室工作等审查学生详细情况的程序,用于提高学生的学士成绩,克服学士成绩低等的困难,从从从电子计算系收集的学士学术学生数据中提取有用的知识,随后采用数据挖掘技术来发现分类和集群,在这项研究中,介绍了基于天真的传说算法和用于学术数据挖掘的分类方法,支持学生与讲师一道评价学术成绩,这是学生提高学习成绩的谨慎方法。