DOC add remark that SGDClassifier partial_fit does not implement learning rate schemes
@@ -823,8 +823,8 @@ class BaseSGDClassifier(LinearClassifierMixin, BaseSGD, metaclass=ABCMeta):
Internally, this method uses ``max_iter = 1``. Therefore, it is not
guaranteed that a minimum of the cost function is reached after calling
- it once. Matters such as objective convergence and early stopping
- should be handled by the user.
+ it once. Matters such as objective convergence, early stopping, and
+ learning rate adjustments should be handled by the user.
Parameters
----------
@@ -2000,7 +2000,8 @@ class SGDOneClassSVM(BaseSGD, OutlierMixin):
instance used by `np.random`.
learning_rate : string, optional
- The learning rate schedule:
+ The learning rate schedule to use with `fit`. (If using `partial_fit`,
+ learning rate must be controlled directly).
'constant':
eta = eta0
