Pushing the docs to dev/ for branch: master, commit ee2508ce45fd7d491b25e354509cda26c14b16ec

Author: sklearn-ci

dev/_downloads/3409d9766d352cc9f9b169d4a799a87a/auto_examples_python.zip

@@ -47,6 +47,24 @@
         "numeric_features = ['age', 'fare']\nnumeric_transformer = Pipeline(steps=[\n    ('imputer', SimpleImputer(strategy='median')),\n    ('scaler', StandardScaler())])\n\ncategorical_features = ['embarked', 'sex', 'pclass']\ncategorical_transformer = Pipeline(steps=[\n    ('imputer', SimpleImputer(strategy='constant', fill_value='missing')),\n    ('onehot', OneHotEncoder(handle_unknown='ignore'))])\n\npreprocessor = ColumnTransformer(\n    transformers=[\n        ('num', numeric_transformer, numeric_features),\n        ('cat', categorical_transformer, categorical_features)])\n\n# Append classifier to preprocessing pipeline.\n# Now we have a full prediction pipeline.\nclf = Pipeline(steps=[('preprocessor', preprocessor),\n                      ('classifier', LogisticRegression())])\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n\nclf.fit(X_train, y_train)\nprint(\"model score: %.3f\" % clf.score(X_test, y_test))"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "HTML representation of ``Pipeline``\n##############################################################################\n When the ``Pipeline`` is printed out in a jupyter notebook an HTML\n representation of the estimator is displayed as follows:\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "from sklearn import set_config\nset_config(display='diagram')\nclf"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},

dev/_downloads/b5a4a1546e908b944c14370f9e7e2a25/plot_column_transformer_mixed_types.ipynb

@@ -87,6 +87,15 @@
 clf.fit(X_train, y_train)
 print("model score: %.3f" % clf.score(X_test, y_test))
 
+##############################################################################
+# HTML representation of ``Pipeline``
+###############################################################################
+# When the ``Pipeline`` is printed out in a jupyter notebook an HTML
+# representation of the estimator is displayed as follows:
+from sklearn import set_config
+set_config(display='diagram')
+clf
+
 ###############################################################################
 # Use ``ColumnTransformer`` by selecting column by data types
 ###############################################################################