Multi-model Stacking Ensemble Learning for Student Achievement Prediction
Author:
Affiliation:
1. Guilin University of Electronic Technology,Guangxi Key Laboratory of Trusted Software,Guilin,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9720298/9720304/09720454.pdf?arnumber=9720454
Reference11 articles.
1. An enhanced bayesian network model for prediction of students' academic performance in engineering programs
2. Early Prediction of Student Success: Mining Students Enrolment Data
3. Gender differences of academic performance in compulsory education in rural Southwestern China
4. How difficult are exams? A framework for assessing the complexity of introductory programming exams;sheard;Australian Computer Society,2013
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1. Classifying Student Achievement Using K-NN Based on Feature Normalization Techniques;2023 International Seminar on Application for Technology of Information and Communication (iSemantic);2023-09-16
2. Explainable Stacking Machine Learning Ensemble for Predicting Airline Customer Satisfaction;Third Congress on Intelligent Systems;2023
3. Improving the Performance of Classification via Clustering on the Students’ Academic Performance using Stacking Algorithm;Lecture Notes in Networks and Systems;2023
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