What is the Residual Standard Error (RSE) in the context of Python regression?

The Residual Standard Error (RSE), often referred to as the standard error of the regression or the root mean squared error (RMSE) when calculated with unscaled residuals, is a measure of the dispersion of the observed values around the regression line. In Python, it quantifies the typical distance between the actual y-values and the y-values predicted by your regression model. A lower RSE indicates that the model's predictions are closer to the actual data points, suggesting a better fit.