Clustering Proficient Students Using Data Mining Approach

被引：0

作者：

Ashok, M. V. ^{[1
]}

Apoorva, A. ^{[2
]}

机构：

[1] Teachers Acad, Dept Comp Sci, Bangalore, Karnataka, India

[2] GIMS, Dept MCA, Bangalore, Karnataka, India

来源：

ADVANCES IN COMPUTING AND DATA SCIENCES, ICACDS 2016 | 2017年 / 721卷

关键词：

Educational data mining; Clustering; Proficient student; KSA; SEGMENTATION;

D O I：

10.1007/978-981-10-5427-3_8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Every educational institution strives to be the best in terms of quality. Quality is measured using many parameters. One such parameter of measuring quality is proficient students. Hence the objective of this study is to Cluster proficient students of an educational institution using data mining approach. Clustering is based on knowledge, skill and ability concept known as KSA. A model and an algorithm are proposed to accomplish the task of Clustering. A student data set consisting of 1,434 students from an institution located in Bangalore are collected for the study and were subjected to preprocessing. To evaluate the performance of the proposed algorithm, it is compared with other Clustering algorithm on the basis of precision and recall. The results obtained are tabulated. The performance of the proposed algorithm was better in comparison with other algorithms.

引用

页码：70 / 80

页数：11

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