In a regression problem, you have trained a model using the mean squared error (MSE) as the loss function. You want to evaluate the performance of your model using the root mean squared error (RMSE). Which of the following steps should you take, and why?

Simulated

Take the square root of the MSE, because the RMSE is the square root of the MSE.

79.3%

Divide the MSE by the number of samples, because the RMSE is the average of the squared errors.

3.4%

Multiply the MSE by the number of samples, because the RMSE is the sum of the squared errors.

3.4%

Do not perform any additional steps, because the MSE is already a measure of error.

13.8%

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