What are some common evaluation metrics for regression models?

Common metrics for regression include:
Mean Absolute Error (MAE): The average of absolute differences between predicted and actual values.
Mean Squared Error (MSE): The average of squared differences between predicted and actual values.
R-squared: Measures the proportion of variance explained by the model.