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calculate root mean square error python

def rmse(predictions, targets):
    return np.sqrt(((predictions - targets) ** 2).mean())
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Root Mean Squared Error python

# Needed packages
from sklearn.metrics import mean_squared_error

#  Values to compare
y_true = [[0.5, 1],[-1, 1],[7, -6]]
y_pred = [[0, 2],[-1, 2],[8, -5]]

# Root mean squared error (by using: squared=False)

rmse = mean_squared_error(y_true, y_pred, squared=False)

print(rmse)
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root mean square python

def rms(x):
    rms = np.sqrt(np.mean(x**2))
    return rms
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