[MRG] DOC Add example about interpretation of coefficients of linear models

build_tools/circle/build_doc.sh

@@ -169,7 +169,7 @@ conda create -n $CONDA_ENV_NAME --yes --quiet python="${PYTHON_VERSION:-*}" \
   cython="${CYTHON_VERSION:-*}" pytest coverage \
   matplotlib="${MATPLOTLIB_VERSION:-*}" sphinx=2.1.2 pillow \
   scikit-image="${SCIKIT_IMAGE_VERSION:-*}" pandas="${PANDAS_VERSION:-*}" \
-  joblib memory_profiler packaging
+  joblib memory_profiler packaging seaborn
 
 source activate testenv
 pip install sphinx-gallery

doc/conf.py

@@ -250,6 +250,7 @@
     'matplotlib': ('https://matplotlib.org/', None),
     'pandas': ('https://pandas.pydata.org/pandas-docs/stable/', None),
     'joblib': ('https://joblib.readthedocs.io/en/latest/', None),
+    'seaborn': ('https://seaborn.pydata.org/', None),
 }
 
 v = parse(release)

doc/developers/contributing.rst

@@ -553,7 +553,8 @@ the development version.
 
 Building the documentation requires installing some additional packages::
 
-    pip install sphinx sphinx-gallery numpydoc matplotlib Pillow pandas scikit-image packaging
+    pip install sphinx sphinx-gallery numpydoc matplotlib Pillow pandas \
+                scikit-image packaging seaborn
 
 To build the documentation, you need to be in the ``doc`` folder::
 

doc/inspection.rst

@@ -17,6 +17,10 @@ predictions from a model and what affects them. This can be used to
 evaluate assumptions and biases of a model, design a better model, or
 to diagnose issues with model performance.
 
+.. topic:: Examples:
+
+   * :ref:`sphx_glr_auto_examples_inspection_plot_linear_model_coefficient_interpretation.py`
+
 .. toctree::
 
     modules/partial_dependence

doc/modules/linear_model.rst

@@ -146,7 +146,7 @@ a linear kernel.
 
    * :ref:`sphx_glr_auto_examples_linear_model_plot_ridge_path.py`
    * :ref:`sphx_glr_auto_examples_text_plot_document_classification_20newsgroups.py`
-
+   * :ref:`sphx_glr_auto_examples_inspection_plot_linear_model_coefficient_interpretation.py`
 
 Ridge Complexity
 ----------------
@@ -232,6 +232,7 @@ computes the coefficients along the full path of possible values.
 
   * :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_and_elasticnet.py`
   * :ref:`sphx_glr_auto_examples_applications_plot_tomography_l1_reconstruction.py`
+  * :ref:`sphx_glr_auto_examples_inspection_plot_linear_model_coefficient_interpretation.py`
 
 
 .. note:: **Feature selection with Lasso**