STUDENT PERFORMANCE ANALYSIS USING CLUSTERING ALGORITHM

被引:0
|
作者
Singh, Ishwank [1 ]
Sabitha, A. Sai [1 ]
Bansal, Abhay [1 ]
机构
[1] Amity Univ Uttar Pradesh, ASET, CSE, Noida, India
关键词
student performance; cluster analysis; K-means algorithm; data mining; overall performance; silhouette measure;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
University and technical organizations are facing high competition and their challenge is in analyzing their performance. The major challenges are in admission, student placement and in the curriculum. The two most important process during which data's are collected and analyzed are admission and placement. The ranking of the university depends on academic performance and placement of the student. Apart from academic performance there are various other factors which help in understanding the overall performance of the student. In this research work, the data mining technique is used to understand the performance of student and group the students under various categories as a student need to consistently improve to compete in today's world.
引用
收藏
页码:294 / 299
页数:6
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