DOC clarify that n_iter_no_change is not just for early-stopping for SGD
@@ -813,6 +813,8 @@ class SGDClassifier(BaseSGDClassifier):
The stopping criterion. If it is not None, training will stop
when (loss > best_loss - tol) for ``n_iter_no_change`` consecutive
epochs.
+ Convergence is checked against the training loss or the
+ validation loss depending on the `early_stopping` parameter.
.. versionadded:: 0.19
@@ -884,7 +886,10 @@ class SGDClassifier(BaseSGDClassifier):
Added 'validation_fraction' option
n_iter_no_change : int, default=5
- Number of iterations with no improvement to wait before early stopping.
+ Number of iterations with no improvement to wait before stopping
+ fitting.
+ Convergence is checked against the training loss or the
+ validation loss depending on the `early_stopping` parameter.
.. versionadded:: 0.20
Added 'n_iter_no_change' option
@@ -1431,6 +1436,8 @@ class SGDRegressor(BaseSGDRegressor):
The stopping criterion. If it is not None, training will stop
when (loss > best_loss - tol) for ``n_iter_no_change`` consecutive
epochs.
+ Convergence is checked against the training loss or the
+ validation loss depending on the `early_stopping` parameter.
.. versionadded:: 0.19
@@ -1495,7 +1502,10 @@ class SGDRegressor(BaseSGDRegressor):
Added 'validation_fraction' option
n_iter_no_change : int, default=5
- Number of iterations with no improvement to wait before early stopping.
+ Number of iterations with no improvement to wait before stopping
+ fitting.
+ Convergence is checked against the training loss or the
+ validation loss depending on the `early_stopping` parameter.
.. versionadded:: 0.20
Added 'n_iter_no_change' option
