DOC make SLEP007 a more prominent (scikit-learn#31037)

Author: lorentzenchr

doc/whats_new/v1.0.rst

@@ -419,7 +419,8 @@ Changelog
 
 - |API| All estimators store `feature_names_in_` when fitted on pandas Dataframes.
   These feature names are compared to names seen in non-`fit` methods, e.g.
-  `transform` and will raise a `FutureWarning` if they are not consistent.
+  `transform` and will raise a `FutureWarning` if they are not consistent, see also
+  :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_0_0.py`.
   These ``FutureWarning`` s will become ``ValueError`` s in 1.2. :pr:`18010` by
   `Thomas Fan`_.
 

examples/release_highlights/plot_release_highlights_1_0_0.py

@@ -140,7 +140,9 @@
 # When an estimator is passed a `pandas' dataframe
 # <https://pandas.pydata.org/docs/user_guide/dsintro.html#dataframe>`_ during
 # :term:`fit`, the estimator will set a `feature_names_in_` attribute
-# containing the feature names. Note that feature names support is only enabled
+# containing the feature names. This is a part of
+# `SLEP007 <https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep007/proposal.html>`__.
+# Note that feature names support is only enabled
 # when the column names in the dataframe are all strings. `feature_names_in_`
 # is used to check that the column names of the dataframe passed in
 # non-:term:`fit`, such as :term:`predict`, are consistent with features in

examples/release_highlights/plot_release_highlights_1_1_0.py

@@ -60,9 +60,11 @@
 # %%
 # `get_feature_names_out` Available in all Transformers
 # -----------------------------------------------------
-# :term:`get_feature_names_out` is now available in all Transformers. This enables
-# :class:`~pipeline.Pipeline` to construct the output feature names for more complex
-# pipelines:
+# :term:`get_feature_names_out` is now available in all transformers, thereby
+# concluding the implementation of
+# `SLEP007 <https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep007/proposal.html>`__.
+# This enables :class:`~pipeline.Pipeline` to construct the output feature names for
+# more complex pipelines:
 from sklearn.compose import ColumnTransformer
 from sklearn.preprocessing import OneHotEncoder, StandardScaler
 from sklearn.pipeline import make_pipeline