ValueError: 'loss' invalid for SGDRegressor

ValueError: SGDRegressor loss invalid

$ python -c "from sklearn.linear_model import SGDRegressor; SGDRegressor(loss='mse2').fit([[0],[1]],[0,1])"
Traceback (most recent call last):
  File "<string>", line 1, in <module>
ValueError: loss must be one of 'squared_error','huber','epsilon_insensitive','squared_epsilon_insensitive'

Why this happens

Loss string isn’t recognized.

Fix

Use a supported loss.

Wrong code

from sklearn.linear_model import SGDRegressor
SGDRegressor(loss='mse2')

Fixed code

from sklearn.linear_model import SGDRegressor
SGDRegressor(loss='squared_error')