How do you evaluate a regression model (MAE, RMSE, R², MAPE)?
Regression calls for different metrics than classification, and each tells its own story. What matters is knowing what RMSE vs MAE vs R² vs MAPE really measure and their failure modes around outliers, scale, and zeros.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Regression calls for different metrics than classification, and each tells its own story. What matters is knowing what RMSE vs MAE vs R² vs MAPE really measure and their failure modes around outliers, scale, and zeros.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
