mean squared error python
from sklearn.metrics import mean_squared_error
mean_squared_error(y_true, y_pred)
mean squared error python
from sklearn.metrics import mean_squared_error
mean_squared_error(y_true, y_pred)
sklearn rmse
from sklearn.metrics import mean_squared_error
rms = mean_squared_error(y_actual, y_predicted, squared=False)
calculate root mean square error python
def rmse(predictions, targets):
return np.sqrt(((predictions - targets) ** 2).mean())
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