Overview
MSE is the standard loss function for predicting continuous numbers (like prices or temperatures). It is calculated by taking the difference between the prediction and the target, squaring it, and averaging the results.
Characteristics
- Squaring the Error: This ensures the result is always positive and penalizes larger errors more heavily than smaller ones.
- Sensitivity to Outliers: Because errors are squared, outliers can have a significant impact on the total loss.
Related Metric
Root Mean Squared Error (RMSE) is the square root of MSE, which brings the error back to the same units as the target variable.