update for issue scikit-learn#6523 (add logistic_regression_path to classes.rst (scikit-learn#6970)

* update for issue scikit-learn#6523 (add logistic_regression_path to classes.rst

* Clarifies statement about no warm-start and no speedup with liblinear

Author: vharavu

doc/modules/classes.rst

@@ -727,6 +727,7 @@ Kernels:
    linear_model.lars_path
    linear_model.lasso_path
    linear_model.lasso_stability_path
+   linear_model.logistic_regression_path
    linear_model.orthogonal_mp
    linear_model.orthogonal_mp_gram
 

sklearn/linear_model/logistic.py

@@ -458,6 +458,8 @@ def logistic_regression_path(X, y, pos_class=None, Cs=10, fit_intercept=True,
     This is an implementation that uses the result of the previous model
     to speed up computations along the set of solutions, making it faster
     than sequentially calling LogisticRegression for the different parameters.
+    Note that there will be no speedup with liblinear solver, since it does
+    not handle warm-starting.
 
     Read more in the :ref:`User Guide <logistic_regression>`.