Lesson 3
Linear Regression
Chapter : Lesson 3
Episode 9 - Evaluation Metrics for Regression
Summary:
- Common metrics for regression:
- Mean Squared Error (MSE) - penalises large errors more than smaller errors
- Mean Absolute Error (MAE) - less sensitive to outliers
- Root Mean Squared Error (RMSE) - more interpretable, less sensitive to outliers than MSE. Most common and preferred.