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Root Mean Squared Error

A regression metric that calculates the square root of the average of squared differences between predicted and actual values.

AbbreviationRMSE
Categoryai

Overview

RMSE is one of the most common metrics for evaluating regression models. It is the square root of the Mean Squared Error (MSE).

Formula

RMSE = √[ (1/n) * Σ (Actual - Predicted)² ]

Characteristics

  • Penalizes Large Errors: Like MSE, it squares the errors, making it sensitive to outliers.
  • Same Units: Taking the square root brings the error back to the same units as the target variable, making it easier to interpret than MSE.

Use Case

Standard metric for many regression tasks where large errors are particularly undesirable.

Related Terms

Mean Absolute ErrorR-squared