RMSE is expressed in the same units as the observed data, making it easy to interpret. A lower RMSE value indicates a better fit between the predicted and observed data, while a higher RMSE suggests poor predictive performance. However, it is important to consider RMSE in conjunction with other metrics like Mean Absolute Error (MAE) and R-squared (R²) for a comprehensive assessment.
