Is there a library function for Root mean square error (RMSE) in python?
Full error message
I know I could implement a root mean squared error function like this:
def rmse(predictions, targets):
return np.sqrt(((predictions - targets) ** 2).mean())
What I'm looking for if this rmse function is implemented in a library somewhere, perhaps in scipy or scikit-learn?Solutionsource: stackoverflow \u2197
sklearn >= 1.4 sklearn.metrics.root_mean_squared_error from sklearn.metrics import root_mean_squared_error rms = root_mean_squared_error(y_actual, y_predicted) sklearn >= 0.22.0 and < 1.4 sklearn.metrics has a mean_squared_error function with a squared kwarg (defaults to True). Setting squared to False will return the RMSE. from sklearn.metrics import mean_squared_error rms = mean_squared_error(y_actual, y_predicted, squared=False)
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