Combining RMSE and R-squared for Better Forecast Model Evaluation
mdancho84 · x · 2026-09-01
In forecasting, maximizing R-squared (variance explained) is not always ideal as it prioritizes fitting variance over stability. The author suggests combining R-squared with Root Mean Squared Error (RMSE): RMSE measures model stability, while R-squared indicates how well the model captures peaks and valleys. This dual-metric approach provides a better picture of model performance.
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