Research on Machine Learning Prediction of Air Quality Index Based on SPSS

Air From autumn to winter, air pollution in North China is very serious. If we can make effective prediction, we can achieve effective prevention. In this paper, SPSS is used to associate a phenomenon with multiple factors through the optimal combination of multiple independent variables. It is more effective and realistic to predict or estimate the dependent variables than to predict or estimate only one independent variable. Regression with two or more independent variables is multivariate linear regression, and multivariate linear regression has more practical significance than univariate linear regression ∘Through the establishment of multiple linear regression model, the factors affecting air quality were screened and analyzed. The factors influencing air quality index were PM2.5, PM10, SO2, NO2, CO and O3. Through regression analysis of one year's data samples, the prediction model is obtained. It has been proved that the prediction method is worth popularizing.