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摘要:
The academic community is currently confronting some challenges in terms of analyzing and evaluating the progress of a student’s academic performance. In the real world, classifying the performance of the students is a scientifically challenging task. Recently, some studies apply cluster analysis for evaluating the students’ results and utilize statistical techniques to part their score in regard to student’s performance. This approach, however, is not efficient. In this study, we combine two techniques, namely, k-mean and elbow clustering algorithm to evaluate the student’s performance. Based on this combination, the results of performance will be more accurate in analyzing and evaluating the progress of the student’s performance. In this study, the methodology has been implemented to define the diverse fascinating model taking the student test scores.
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篇名 Clustering Approach for Analyzing the Student’s Efficiency and Performance Based on Data
来源期刊 数据分析和信息处理(英文) 学科 文学
关键词 K-Means Technique Elbow Technique Clustering Technique Data Mining Academic Performance
年,卷(期) 2020,(3) 所属期刊栏目
研究方向 页码范围 171-182
页数 12页 分类号 H31
字数 语种
DOI
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研究主题发展历程
节点文献
K-Means
Technique
Elbow
Technique
Clustering
Technique
Data
Mining
Academic
Performance
研究起点
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研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
数据分析和信息处理(英文)
季刊
2327-7211
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
106
总下载数(次)
0
总被引数(次)
0
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