Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/8283
Title: Data visualization and analysis with machine learning for the USA’s COVID-19 prediction
Authors: Dr. YUEN Man-Ching, Connie 
Cheng, Wing-Fat 
Wong, Hiu-Hong 
Issue Date: 2022
Source: Yuen, Man-Ching, Cheng, Wing-Fat & Wong, Hiu-Hong (2022 Nov 4-7). Data visualization and analysis with machine learning for the USA’s COVID-19 prediction. In Tallón-Ballesteros, Antonio J. (Ed.). Fuzzy systems and data mining VIII: Proceedings of FSDM 2022. FSDM 2022 : 8th International Conference on Fuzzy Systems and Data Mining, Xiamen, China (pp. 181-190). IOS Press.
Conference: FSDM 2022 : 8th International Conference on Fuzzy Systems and Data Mining 
Abstract: Recently, many research works adopt machine learning to provide accurate predictions on the COVID-19 pandemic. In this paper, we design and develop a web system which adopts machine learning methodologies to provide data analysis and data visualization. For experiment analytics results in the system, we find that SVM method outperforms LR method in every use case. We propose a web-based user-friendly and intuitive COVID-19 information hub, which can improve data accessibility to the public and allow more accurate decision-making to help fight the pandemic.
Type: Conference Paper
URI: http://hdl.handle.net/20.500.11861/8283
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