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AI & Machine Learning · Foundational

Root Mean Squared Error (RMSE)

The square root of MSE, expressing typical prediction error in the target's own units.

Definition

RMSE is widely used to report regression accuracy because it shares the target's units while still weighting large errors heavily. Lower is better. It is always greater than or equal to MAE.

Example

An RMSE of 12,000 for house prices means typical errors around $12,000, with large misses weighted more.

Exam tip

RMSE is the default AWS and Azure regression metric in many exam scenarios.

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