Adding newton-cg solver for multinomial case.
Add comments to _multinomial_loss_grad_hess function.
Fixed pep8 errors. Added docstring for _multinomial_loss.
Fixing docstring on _multinomial_loss.
Fixing more pep8 errors.
Merge remote-tracking branch 'upstream/master' into multinomial_newtoncg
Removed some unnecessary lines and reformatted for consistency in _multinomial_loss and _multinomial_loss_grad_hess.
Modified parameter description in docstring of
_multinomial_loss_grad_hess.
Adding test cases for multinomial LogisticRegression using newton-cg
solver.
Modified hessp function in _multinomial_loss_grad_hess to compute r_yhat
in place.
Simplied conditional statements that branches based on solver +
multi_class input combinations.
Extended tests on multinomial LogisticRegression to include newton-cg
solver case.
Updated doc string of LogisticRegression to include newton-cg solver in
multinomial case.
Update whats_new.rst. Add contact information to logistic.py.
Modified doc/modules/linear_model.rst to incorporate the newton-cg solver
option for multi_class="multinomial".
Minor doc and formatting changes.
Reformatted docstrings in multinomial functions. Refactored multinomial
functions to avoid duplicating code.
Wrap _multinomial_loss_grad in lambda function for passing into lbfgs.
Modify shape check on coef matrix in _logistic_regression_path.
Merge pull request #3646 from s8wu/multinomial_newtoncg

[MRG+2] Multinomial newtoncg
Add quantile strategy to DummyRegressor. Fixes #3421.
Update what's new
Expose positive option in elasticnet and lasso path