This paper investigates the prediction method for tar yield based on correlation analysis and machine learning. Initially, to address the issue of missing values in the data, this study employs cubic spline interpolation for imputation. By constructing the interpolation function and setting constraint conditions, the data imputation process was successfully completed. Subsequently, this paper conducts Pearson and Spearman correlation analyses to assess the linear and nonlinear relationships between different variables, and the results of the correlation analysis are displayed through heatmaps....
