Multi-split optimized bagging ensemble model selection for multi-class educational data mining

Author:

Injadat MohammadNoorORCID,Moubayed Abdallah,Nassif Ali Bou,Shami Abdallah

Funder

Government of Ontario

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference66 articles.

1. Abdul Aziz A, Ismail NH, Ahmad F (2013) Mining students’ academic performance. Journal of Theoretical and Applied Information Technology 53(3):485–485

2. Ahmed ABED, Elaraby IS (2014) Data mining: a prediction for student’s performance using classification method. World Journal of Computer Application and Technology 2(2):43–47

3. Aly M (2005) Survey on multiclass classification methods. Neural Network 19:1–9

4. Asogbon MG, Samuel OW, Omisore MO, Ojokoh BA (2016) A multi-class support vector machine approach for students academic performance prediction. Int J Multidisciplinary and Current Research 4

5. Athani SS, Kodli SA, Banavasi MN, Hiremath PS (2017) Student performance predictor using multiclass support vector classification algorithm. In: 2017 international conference on signal processing and communication (ICSPC). IEEE, pp 341–346

Cited by 55 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A comprehensive ensemble pruning framework based on dual-objective maximization trade-off;Knowledge and Information Systems;2024-05-10

2. Intrusion detection system: a deep neural network-based concatenated approach;The Journal of Supercomputing;2024-03-12

3. A short-term photovoltaic output power forecasting based on ensemble algorithms using hyperparameter optimization;Electrical Engineering;2024-02-26

4. Systematic Review and Analysis of EDM for Predicting the Academic Performance of Students;Journal of The Institution of Engineers (India): Series B;2024-02-04

5. Online Courses Student Performance Prediction with Multi-model Stacking Ensemble Classifier;Proceedings of the 3rd International Conference on Computer, Artificial Intelligence and Control Engineering;2024-01-26

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3