Application of improved recursive regression algorithm on I&O model under COVID-19

Regression algorithm is an important data prediction method of machine learning. It can establish calculation matrix through the existing data and obtain the hidden characteristics in the data and other valuable information. Due to the excellent data processing ability, regression is widely used in gray data prediction, algorithm model building, data analysis and other fields. In this paper, the multi-layer recursive regression is adopted and improved for the regression algorithm with double influence factors, which increases the processing ability of multi class data. Data of import and export trade between China and the United States in the past five years is collected to create the future prediction model when the epidemic does not occur. Meanwhile, the data of four months after the outbreak to calculate the condition of the future prediction model of the epidemic situation in COVID-19. Using two opposite conditions as different data of regression algorithm calculation, different prediction algorithm formulas are obtained. After multiple calculations, the average value increases the sensitivity of the model. The calculation results show that the improved recursive regression algorithm has higher stability and sensitivity.