Student's Performance Evaluation Using Ensemble Machine Learning Algorithms
Journal Title: Engineering and Technology Journal - Year 2024, Vol 9, Issue 08
Abstract
This study explores the critical domain of predicting students' academic performance in educational institutions. By harnessing the potential of machine learning algorithms, specifically Random Forest, KNN, and XGBoost, and leveraging data collected through technology-enhanced learning applications, the research aims to provide valuable insights into the factors influencing academic outcomes based on the dataset obtained from Kaggle. It is important to note that these models were also hybridized using the stacking ensemble approach. The performances of the algorithm were evaluated using the Root Mean Squared Error (RMSE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared (R2) score. Resultively, the stacked ensemble model displayed remarkable results, with an impressively low RMSE of 0.1768, MSE of 0.0312, MAE of 0.1247, and a high R2-score of 0.9705. This finding showed that the Ensemble model, which combines the strengths of the Random Forest, KNN, and XGBoost algorithms, provides the best overall prediction accuracy, with a high degree of correlation between predicted and actual student performance.
Authors and Affiliations
Oladunjoye John Abiodun , Andrew Ishaku Wreford,
ARTIFICIAL NEURAL NETWORK AND THEIR APPLICATIONS IN FOOD MATERIALS: A REVIEW
This paper is a review of artificial neural network technique for the prediction of drying parameters of food materials. The meaning of ANN, the importance, areas that ANN could be applied, future prospects and summary o...
Performance Evaluation of a Locally Produced Pulse Oximeter
Most aftermarket pulse oximeters (POs) sold usually have peripheral blood oxygen saturation (SpO2) sensors with short life spans and the lack of specialized personnel to carry out the repairs result in frequent failures...
The Future of Electric Vehicles: Technological Innovations and Market Trends
The future of electric vehicles (EVs) is shaped by rapid technological innovations and evolving market trends that promise to revolutionize the automotive industry and accelerate the transition towards sustainable transp...
Development of Electronic Health Record System Functionality through the Creation of a Central Surgery Module
With the advancement of health technology, the use of Electronic Health Records (EHR) systems has become crucial in improving the efficiency and quality of services in various hospital units. However, the adoption of EHR...
LINEAR ANALYSIS OF COMPOSITE LAMINATED PLATES USING FIRST ORDER SHEAR DEFORMABLE THEORY
Dynamic Relaxation (DR) method is presented for the analysis of geometrically linear laterally loaded, rectangular laminated plates. The analysis uses the Mindlin plate theory which accounts for transverse shear deformat...