Pushing the docs to dev/ for branch: main, commit c5f10c8b51003caa1feb90b1c6cdd3f73615e45f

Author: sklearn-ci

dev/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: ea12d9328b050dfe2b25925462d8d523
+config: 1e5ac10e7271b57825afd6df76e907a9
 tags: 645f666f9bcd5a90fca523b33c5a78b7

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -106,7 +106,7 @@
 # :class:`OneHotEncoder` supports aggregating infrequent categories into a single
 # output for each feature. The parameters to enable the gathering of infrequent
 # categories are `min_frequency` and `max_categories`. See the
-# :ref:`User Guide <one_hot_encoder_infrequent_categories>` for more details.
+# :ref:`User Guide <encoder_infrequent_categories>` for more details.
 from sklearn.preprocessing import OneHotEncoder
 import numpy as np
 

dev/_downloads/4cf0456267ced0f869a458ef4776d4c5/plot_release_highlights_1_1_0.py

@@ -65,7 +65,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Grouping infrequent categories in :class:`OneHotEncoder`\n:class:`OneHotEncoder` supports aggregating infrequent categories into a single\noutput for each feature. The parameters to enable the gathering of infrequent\ncategories are `min_frequency` and `max_categories`. See the\n`User Guide <one_hot_encoder_infrequent_categories>` for more details.\n\n"
+        "## Grouping infrequent categories in :class:`OneHotEncoder`\n:class:`OneHotEncoder` supports aggregating infrequent categories into a single\noutput for each feature. The parameters to enable the gathering of infrequent\ncategories are `min_frequency` and `max_categories`. See the\n`User Guide <encoder_infrequent_categories>` for more details.\n\n"
       ]
     },
     {