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Library/ Machine Learning (Supervised + Unsupervised)/ Supervised Learning by Building/ S02 · Build: An Evaluation Harness (used for every model)

subtopic

Regression metrics

10 min applied10 min research1 curated resources

Write evaluate_regressor(y_true, y_pred) returning MAE, RMSE, MAPE, R², peak-hour MAE and under-forecast share. Concepts: MAE; MSE; RMSE; R²; MAPE; error by segment; asymmetric error Project A: Not applicable (classification). Equivalent: cost per decision. Project B: Main metrics: MAE, RMSE, peak-hour MAE (top 10% load hours), under-forecast %.

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Regression metrics · 1x1labs.ai