Pushing the docs to dev/ for branch: master, commit 19c8b1933b9ee301ccdbfbb3f165f314ee168bbf

Author: sklearn-ci

dev/_downloads/21b82d82985712b5de6347f382c77c86/plot_partial_dependence.ipynb

@@ -51,7 +51,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "1-way partial dependence with different models\n----------------------------------------------\n\nIn this section, we will compute 1-way partial dependence with two different\nmachine-learning models: (i) a multi-layer perceptron and (ii) a\ngradient-boosting. With these two models, we illustrate how to compute and\ninterpret both partial dependence plot (PDP) and individual conditional\nexpectation (ICE).\n\nMulti-layer perceptron\n......................\n\nLet's fit a :class:`sklearn.neural_network.MLPRegressor` and compute\nsingle-variable partial dependence plots.\n\n"
+        "1-way partial dependence with different models\n----------------------------------------------\n\nIn this section, we will compute 1-way partial dependence with two different\nmachine-learning models: (i) a multi-layer perceptron and (ii) a\ngradient-boosting. With these two models, we illustrate how to compute and\ninterpret both partial dependence plot (PDP) and individual conditional\nexpectation (ICE).\n\nMulti-layer perceptron\n......................\n\nLet's fit a :class:`~sklearn.neural_network.MLPRegressor` and compute\nsingle-variable partial dependence plots.\n\n"
       ]
     },
     {
@@ -87,7 +87,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "Gradient boosting\n.................\n\nLet's now fit a :class:`sklearn.ensemble.HistGradientBoostingRegressor` and\ncompute the partial dependence on the same features.\n\n"
+        "Gradient boosting\n.................\n\nLet's now fit a :class:`~sklearn.ensemble.HistGradientBoostingRegressor` and\ncompute the partial dependence on the same features.\n\n"
       ]
     },
     {

dev/_downloads/3409d9766d352cc9f9b169d4a799a87a/auto_examples_python.zip

@@ -70,7 +70,7 @@
 # Multi-layer perceptron
 # ......................
 #
-# Let's fit a :class:`sklearn.neural_network.MLPRegressor` and compute
+# Let's fit a :class:`~sklearn.neural_network.MLPRegressor` and compute
 # single-variable partial dependence plots.
 
 from time import time
@@ -131,7 +131,7 @@
 # Gradient boosting
 # .................
 #
-# Let's now fit a :class:`sklearn.ensemble.HistGradientBoostingRegressor` and
+# Let's now fit a :class:`~sklearn.ensemble.HistGradientBoostingRegressor` and
 # compute the partial dependence on the same features.
 
 from sklearn.experimental import enable_hist_gradient_boosting  # noqa