Researchers used polynomial regression theory to create a thermal error compensation model for machine tools. By analyzing correlation coefficients, they identified and removed irrelevant variables, improving the model's accuracy. This method reduced the coupling of temperature variables and saved time compared to traditional regression techniques. The model was validated to have high precision through residual errors and fitting charts.