What are the differences between MSE and RMSE

MSE (Mean Squared Error) represents the difference between the original and predicted values which are extracted by squaring the average difference over the data set. It is a measure of how close a fitted line is to actual data points. The lesser the Mean Squared Error, the closer the fit is to the data set. The MSE has the units squared of whatever is plotted on the vertical axis.

RMSE (Root Mean Squared Error) is the error rate by the square root of MSE. RMSE is the most easily interpreted statistic, as it has the same units as the quantity plotted on the vertical axis or Y-axis. RMSE can be directly interpreted in terms of measurement units, and hence it is a better measure of fit than a correlation coefficient.