… This review investigates the application of different techniques of data mining and … dropout
prediction using machine learning techniques through a review of related research based on …

… performance of the resampling methods better in solving the imbalanced problem, this paper
uses various machine learning … XG-boost, Support Vector Machine (Radial Basis Function), …

… Running out of STEM: A comparative study across STEM majors of college students At-Risk
of dropping out early. In Proceedings of the 8th International Conference on …

… best results for solving student performance prediction tasks. … analysis and comparison of
state of the art machine learning … Comparative analysis of different state of the art techniques …

… aim, through a systematic survey, to understand the landscape of student outcomes prediction
using data mining and machine … study using machine learning to make early predictions of …

… Towards final scores prediction over clickstream using machine learning methods. In
Proceedings of the ICCE 2018—26th International Conference on Computers in Education, …

… However, such studies either emphasize on predicting at-risk students or analyse the … this
study, we intend to analyse student performance through the initiation of different performance-…

… aims to develop efficient data-driven models to accurately forecast wind power generation. …
Firstly, we investigate the performance of enhanced machine learning models to forecast …

… LMSs) allow teachers to study student performances using logged student data, but teachers
… This study used machine learning algorithms to predict individual students’ difficulties in the …

… early-stage heart disease prediction by analytical support of … This study aimed to identify
machine learning classifiers with … machine-learning algorithms were applied and compared for …