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The term 'root mean squared error' is correct, and can be used in written English.
You can use this term when talking about the measure of accuracy of a predictive model, and comparing the differences between the actual values and the predicted values. For example, "We were able to determine that our predictive model had an RMSE (root mean squared error) of 4.2, indicating that it was fairly accurate in its predictions."
Exact(57)
Finally, the root mean squared error (RMSE) is calculated from the square root of MSE.
root mean squared error of prediction.
The root mean squared error (RMSE) is evaluated by.
RMSE root mean squared error, MAE mean absolute error.
Figure 5 The root mean squared error of timing estimator.
The root mean squared error of calibration (RMSEC) is 0.0503 and the root mean squared error of validation (RMSEV) is 0.0485.
In the former the root mean squared error of prediction (RMSEP) was 0.42 0.50% SOC.
Root mean squared error and correlation coefficient were evaluated as performance criteria.
The root mean squared error was 0.03 mm, which is the effective precision of the method.
These parameters minimize the root mean squared error of the model.
Similar(1)
The estimations are compared to the actual values using a root-mean squared error (RMSE).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com