Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/8283
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dc.contributor.authorDr. YUEN Man-Ching, Connieen_US
dc.contributor.authorCheng, Wing-Faten_US
dc.contributor.authorWong, Hiu-Hongen_US
dc.date.accessioned2023-10-17T08:17:14Z-
dc.date.available2023-10-17T08:17:14Z-
dc.date.issued2022-
dc.identifier.citationYuen, 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.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11861/8283-
dc.description.abstractRecently, 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.en_US
dc.language.isoenen_US
dc.titleData visualization and analysis with machine learning for the USA’s COVID-19 predictionen_US
dc.typeConference Paperen_US
dc.relation.conferenceFSDM 2022 : 8th International Conference on Fuzzy Systems and Data Miningen_US
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
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