What metrics are used to evaluate Linear Regression?

Updated May 16, 2026

Short answer

Common metrics include MAE, MSE, RMSE, and R².

Deep explanation

These metrics measure different aspects of prediction error, from average error magnitude to variance explained.

Real-world example

Evaluating demand forecasting models.

Common mistakes

  • Using only one metric blindly.

Follow-up questions

  • When is MAE preferred over MSE?

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