Application of hybrid clustering methods for student performance evaluation

被引:2
|
作者
Yadav R.S. [1 ]
机构
[1] Department of Computer Science and Engineering, Ashoka Institute of Technology and Management, Engineering Chauraha, Paharia, Sarnath, Varanasi, 221007, Uttar Pradesh
关键词
Academic performance; Fuzzy C-Means; Fuzzy inference; Fuzzy logic; Subtractive Clustering;
D O I
10.1007/s41870-018-0192-2
中图分类号
学科分类号
摘要
In the present research paper, an attempt has been made to design for evaluating the assessment of student in the educational environment by using the hybrid clustering methods. Various issues along problems are associated with the academic performance evaluation in the field of education. The proposed new approach known as hybrid clustering is based on integrated techniques of Subtractive and Fuzzy C-Means clustering methods. The assessment of student academic performance can be considered as a clustering problem. The clusters are formed on the basis of the intelligence level of students. The intelligence level wise grouping is essential for maintaining the homogeneity of the group. Otherwise it would be difficult to provide good educational services to the highly diverse student population. © 2018, Bharati Vidyapeeth's Institute of Computer Applications and Management.
引用
收藏
页码:749 / 756
页数:7
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