R-squared › Comparison with Other Metrics

R-squared is just one of many regression evaluation metrics. While R-squared measures the proportion of variance explained, other metrics provide different insights: RMSE and MAE assess absolute prediction errors, AIC and BIC help with model selection, and cross-validation evaluates out-of-sample performance. R-squared is excellent for quick assessment of model fit and communicating results to non-technical audiences, but for understanding prediction errors, use RMSE or MAE; for model selection, use AIC or BIC; and for out-of-sample performance, use cross-validation.