DOC explain the difference between `LassoCV` and `Lasso` + `GridSearchCV`
@@ -1884,6 +1884,14 @@ class LassoCV(RegressorMixin, LinearModelCV):
:ref:`examples/linear_model/plot_lasso_model_selection.py
<sphx_glr_auto_examples_linear_model_plot_lasso_model_selection.py>`.
+ :class:`LassoCV` leads to different results than a hyperparameter
+ search using :class:`~sklearn.model_selection.GridSearchCV` with a
+ :class:`Lasso` model. In :class:`LassoCV`, a model for a given
+ penalty `alpha` is warm started using the coefficients of the
+ closest model (trained at the previous iteration) on the
+ regularization path. It tends to speed up the hyperparameter
+ search.
+
Examples
--------
>>> from sklearn.linear_model import LassoCV
