DOC fix incorrect docstring in logistic_regression_path
@@ -543,8 +543,8 @@ def logistic_regression_path(X, y, pos_class=None, Cs=10, fit_intercept=True,
Multiclass option can be either 'ovr' or 'multinomial'. If the option
chosen is 'ovr', then a binary problem is fit for each label. Else
the loss minimised is the multinomial loss fit across
- the entire probability distribution. Works only for the 'lbfgs' and
- 'newton-cg' solvers.
+ the entire probability distribution. Does not work for 'liblinear'
+ solver.
random_state : int, RandomState instance or None, optional, default None
The seed of the pseudo random number generator to use when shuffling
@@ -864,8 +864,8 @@ def _log_reg_scoring_path(X, y, train, test, pos_class=None, Cs=10,
Multiclass option can be either 'ovr' or 'multinomial'. If the option
chosen is 'ovr', then a binary problem is fit for each label. Else
the loss minimised is the multinomial loss fit across
- the entire probability distribution. Does not work for
- liblinear solver.
+ the entire probability distribution. Does not work for 'liblinear'
+ solver.
random_state : int, RandomState instance or None, optional, default None
The seed of the pseudo random number generator to use when shuffling
@@ -1071,7 +1071,7 @@ class LogisticRegression(BaseEstimator, LinearClassifierMixin,
Multiclass option can be either 'ovr' or 'multinomial'. If the option
chosen is 'ovr', then a binary problem is fit for each label. Else
the loss minimised is the multinomial loss fit across
- the entire probability distribution. Does not work for liblinear
+ the entire probability distribution. Does not work for 'liblinear'
solver.
.. versionadded:: 0.18
@@ -1500,8 +1500,8 @@ class LogisticRegressionCV(LogisticRegression, BaseEstimator,
Multiclass option can be either 'ovr' or 'multinomial'. If the option
chosen is 'ovr', then a binary problem is fit for each label. Else
the loss minimised is the multinomial loss fit across
- the entire probability distribution. Works only for the 'newton-cg',
- 'sag', 'saga' and 'lbfgs' solver.
+ the entire probability distribution. Does not work for 'liblinear'
+ solver.
.. versionadded:: 0.18
Stochastic Average Gradient descent solver for 'multinomial' case.
