A Comprehensive Study on Machine Learning Approaches for IoT Data Classification
Keywords:
Keywords: Internet of Things, Data classification, Decision making, CatBoost classifier.Abstract
The exponential growth of the Internet of Things (IoT) has led to vast amounts of data being generated,requiring efficient classification methods for real-time analysis and decision-making. Traditionalclassification techniques often struggle with high-dimensional, imbalanced IoT data, affectingpredictive performance.
References
Xie, S.; Zhang, J. Sensor-Based Exercise Rehabilitation Robot Training Method. J. Sens. 2023, 2023, 7881084.
Qiu, S.; Zhao, H.; Jiang, N.; Wang, Z.; Liu, L.; An, Y.; Zhao, H.; Miao, X.; Liu, R.; Fortino, G. Multi-Sensor Information Fusion Based on Machine Learning for Real Applications in Human Activity Recognition: State-of-the-Art and Research Challenges. Inf. Fusion 2022, 80, 241–265.
Downloads
Published
2025-04-10
How to Cite
Hima Bindu Paka, Gaddam Nandini, Bodhireddy Shruthi, Damera Sanjay, Gaddala Manideep Babu. (2025). A Comprehensive Study on Machine Learning Approaches for IoT Data Classification . Journal of Computational Analysis and Applications (JoCAAA), 34(4), 178–187. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2286
Issue
Section
Articles
