Towards the Selection of Distance Metrics for k-NN Classifier in Students' Performance Prediction Modeling

• Main Authors: Khan I., Mohamed Zabil M.H., Ahmad A.R., Jabeur N.
• Other Authors: 58061521900
• Format: Conference Paper
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Subjects: Chebyshev; Euclidean; k-Nearest Neighbor (k-NN); Machine Learning; Manhattan; Students' Performance Prediction; Machine learning; Nearest neighbor search; Students; Distance metrics; K-near neighbor; Machine-learning; Manhattans; Performance prediction; Performance prediction models; Student performance; Student' performance prediction; Forecasting
• Institution: Universiti Tenaga Nasional

This paper investigates the impact of changing distance metrics on the performance of the k-NN classifier. The study investigates the variation in models performance with changing distance metric and value of k in the context of students' performance prediction models. The research utilizes dat...