DOC add example to combine penatly and datafit (#11)

Author: mathurinm

.github/workflows/circleci.yml

@@ -0,0 +1,13 @@
+name: circleci-redirector
+on: [status]
+jobs:
+  circleci_artifacts_redirector_job:
+    runs-on: ubuntu-latest
+    name: Run CircleCI artifacts redirector
+    steps:
+      - name: GitHub Action step
+        uses: larsoner/circleci-artifacts-redirector-action@master
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+          artifact-path: 0/dev/index.html
+          circleci-jobs: build_docs

doc/add.rst

@@ -4,6 +4,15 @@
 
 With skglm, you can solve any custom Generalized Linear Model with arbitrary smooth datafit and arbitrary proximable penalty, by defining two classes: a ``Penalty`` and a ``Datafit``.
 
+They can then be passed to a :class:`~skglm.GeneralizedLinearEstimator`, using ``is_classif`` to specify if the task is classification or regression.
+
+
+.. code-block:: python
+
+   clf = GeneralizedLinearEstimator(
+      MyDatafit(), MyPenalty(), is_classif=True
+   )
+
 
 How to add a custom penalty
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~

doc/api.rst

@@ -14,6 +14,7 @@ Estimators
 .. autosummary::
    :toctree: generated/
 
+   GeneralizedLinearEstimator
    ElasticNet
    Lasso
    LinearSVC

doc/conf.py

@@ -331,7 +331,8 @@
 }
 
 sphinx_gallery_conf = {
-    'backreferences_dir': 'gen_modules/backreferences',
+    # 'backreferences_dir': 'gen_modules/backreferences',
+    'backreferences_dir': 'generated',
     'doc_module': ('skglm', 'sklearn', 'benchopt'),
     'examples_dirs': '../examples',
     'gallery_dirs': 'auto_examples',