Ultimate access to all questions.
Upgrade Now 🚀
Sign in to unlock AI tutor
Discuss the evaluation metrics that AutoML can use for regression problems. Explain how each metric quantifies the performance of a regression model and which scenarios each metric is most suitable for.
A
Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared (R²), and Mean Percentage Error (MPE).
B
Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), Adjusted R-squared, and Median Absolute Deviation (MAD).
C
Root Mean Squared Logarithmic Error (RMSLE), Coefficient of Determination (R²), Mean Bias Deviation (MBD), and Mean Absolute Scaled Error (MASE).
D
Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared (R²), and Mean Absolute Percentage Error (MAPE).
