Is there a library function for Root mean square error (RMSE) in python?

Question

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?

Answer 1

sklearn >= 0.22.0

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)

sklearn < 0.22.0

sklearn.metrics has a mean_squared_error function. The RMSE is just the square root of whatever it returns.

from sklearn.metrics import mean_squared_error
from math import sqrt

rms = sqrt(mean_squared_error(y_actual, y_predicted))