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AI & Machine Learning · Foundational

Mean Squared Error (MSE)

The average of squared differences between predicted and actual values.

Definition

MSE is a common regression loss and metric. Squaring heavily penalizes large errors, making it sensitive to outliers. Its units are the square of the target units, so RMSE is usually reported for interpretability.

Exam tip

MSE punishes large errors more than MAE does.

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