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9 changes: 8 additions & 1 deletion doc/modules/linear_model.rst
Original file line number Diff line number Diff line change
Expand Up @@ -735,7 +735,14 @@ of a single trial are modeled using a
Logistic regression is implemented in :class:`LogisticRegression`.
This implementation can fit binary, One-vs-Rest, or multinomial logistic
regression with optional :math:`\ell_1`, :math:`\ell_2` or Elastic-Net
regularization. Note that regularization is applied by default.
regularization.

.. note::

Regularization is applied by default, which is common in machine
learning but not in statistics. Another advantage of regularization is
that it improves numerical stability. No regularization amounts to
setting C to a very high value.

As an optimization problem, binary class :math:`\ell_2` penalized logistic
regression minimizes the following cost function:
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