使用机器学习模型进行时间序列Covid - 19预测

Jagadishwari V
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引用次数: 1

摘要

2020年伊始,covid-19大流行爆发,它起源于中国,并迅速蔓延到世界其他地区。这种致命的病毒严重影响了人类的健康和经济。这项工作旨在建立机器学习模型来预测Covid -19的传播。分析中使用最新的Covid - 19时间序列数据集。实现了回归、支持向量机和FBProphet三种预测模型。对这些模型得到的结果进行了研究。与其他模型相比,FBProphet给出了有希望的结果。FBProphet的趋势和季节性成分在时间序列数据分析中非常有用。
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Time series Covid 19 Predictions with Machine Learning Models
The year 2020 began with the outbreak of covid-19 Pandemic, it originated in China and very quickly spread to all the other parts of the world. The deadly virus badly affected the health and economy of Mankind. This work aims to build Machine learning models to predict the spread of Covid -19. The up to date Time series data set of Covid 19 is used in the analytics. Three prediction models namely Regression, SVM and FBProphet are implemented. The results obtained from these models are investigated. FBProphet gives promising results as compared to the other models. The trend and seasonality components of FBProphet are shown to be very useful in the analysis of Time Series Data.
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