Mean Squared Error (MSE)

Mean squared error measures error in a model. If a model does not have any errors, then $MSE=0$. As the error goes up, MSE goes up.

$$MSE=\frac{{\sum }_i^n(y_i-{\hat{y}}_i{)}^2}{n}$$