Mean Squared Error

A metric for regression tasks that measures the average of the squared differences between predicted and actual values. Squaring the errors means large mistakes are penalized much more heavily than small ones, making MSE sensitive to outliers. It is widely used both as a loss function during training and as an evaluation metric.