How do I evaluate the performance of my regression model?

How do I evaluate the performance of my regression model?

You can evaluate a regression model using metrics like R-squared, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). Which metric are you interested in?

What is R-squared and how is it calculated?

R-squared measures the proportion of variance in the dependent variable that can be explained by the independent variables. It's calculated as 1 minus the ratio of the residual sum of squares to the total sum of squares.

What are some common pitfalls when interpreting R-squared?

Common pitfalls include assuming a high R-squared means a good model, ignoring the context of the data, and not considering overfitting.

Can you explain Mean Absolute Error?

Mean Absolute Error (MAE) is the average of the absolute differences between predicted and actual values. It gives a clear idea of the average error in your predictions.