Data visualization and analysis with machine learning for the USA’s COVID-19 prediction

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.