Identifying Factors in COVID - 19 AI Case Predictions
2020 7th International Conference on Soft Computing & Machine Intelligence (ISCMI)(2020)
摘要
Many machine learning methods are being developed to predict the spread of COVID - 19. This paper focuses on the expansion of inputs that may be considered in these models. A correlation matrix is used to identify those variables with the highest correlation to COVID - 19 cases. These variables are then used and compared in three methods that predict future cases: a Support Vector Machine Regression (SVR), Multidimensional Regression with Interactions, and the Stepwise Regression method. All three methods predict a rise in cases similar to the actual rise in cases, and importantly, are all able to predict to a certain degree the unexpected dip in cases on the 10th and 11th day of prediction.
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关键词
COVID - 19,Infectious Diseases,Artificial Intelligence,Support Vector Machine,Correlation
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