Root-mean-square error

The root-mean-square error (RMSE) is a measure of the error and quality of fit of a machine learning model. It’s defined as the square root of the mean squared error.

$$\text{RMSE}=\sqrt{\frac{1}{n}\sum _{i=1}^n(y_i-\hat{f}(x_i){)}^2}$$