Error in the Units of y
Why MAE, MSE and RMSE can report three different numbers for the same predictions, why RMSE is never below MAE, what their ratio tells you about outliers, and why scikit-learn hands back a negative mean squared error.
6 docs tagged with "Metrics"
Scoring a fitted model — what each number measures, what units it is in, and when it misleads.
View all tagsModule 1 Practice Problems
30 practice problems covering linear regression, multiple regression, bias-variance, and error metrics
Module 2 Practice Problems
40 practice problems covering cross-validation, logistic regression, classification metrics, model comparison, and decision boundaries
Performance Metrics & Evaluation
Complete guide to regression and classification metrics with worked examples and interpretations for CT exam
R², Adjusted R² and MAPE
Settles why R² can exceed 1 or go negative, why SST = SSR + SSE only holds for a least-squares fit, why adding a junk feature never lowers R² but does lower Adjusted R², and why scikit-learn's MAPE returns 0.0296 rather than 2.96%.
Residual Analysis and Choosing a Metric
What residuals reveal about model fit, interpreting diagnostic plots, and deciding which evaluation metric to report under problem constraints.