DOC Ensures that MultiTaskLassoCV passes numpydoc validation (#21256)

Pinky-Chaudhary · glemaitre · web-flow · commit c3f41ae198e7 · 2021-10-21T11:25:55.000+02:00
Co-authored-by: Guillaume Lemaitre &lt;g.lemaitre58@gmail.com&gt;
diff --git a/maint_tools/test_docstrings.py b/maint_tools/test_docstrings.py
@@ -18,7 +18,6 @@
     "LabelSpreading",
     "LocallyLinearEmbedding",
     "MultiTaskElasticNetCV",
-    "MultiTaskLassoCV",
     "OrthogonalMatchingPursuitCV",
     "PassiveAggressiveRegressor",
     "SpectralBiclustering",
diff --git a/sklearn/linear_model/_coordinate_descent.py b/sklearn/linear_model/_coordinate_descent.py
@@ -2996,6 +2996,22 @@ class MultiTaskLassoCV(RegressorMixin, LinearModelCV):
 
         .. versionadded:: 1.0
 
+    See Also
+    --------
+    MultiTaskElasticNet : Multi-task ElasticNet model trained with L1/L2
+        mixed-norm as regularizer.
+    ElasticNetCV : Elastic net model with best model selection by
+        cross-validation.
+    MultiTaskElasticNetCV : Multi-task L1/L2 ElasticNet with built-in
+        cross-validation.
+
+    Notes
+    -----
+    The algorithm used to fit the model is coordinate descent.
+
+    To avoid unnecessary memory duplication the X and y arguments of the fit
+    method should be directly passed as Fortran-contiguous numpy arrays.
+
     Examples
     --------
     >>> from sklearn.linear_model import MultiTaskLassoCV
@@ -3009,19 +3025,6 @@ class MultiTaskLassoCV(RegressorMixin, LinearModelCV):
     0.5713...
     >>> reg.predict(X[:1,])
     array([[153.7971...,  94.9015...]])
-
-    See Also
-    --------
-    MultiTaskElasticNet
-    ElasticNetCV
-    MultiTaskElasticNetCV
-
-    Notes
-    -----
-    The algorithm used to fit the model is coordinate descent.
-
-    To avoid unnecessary memory duplication the X and y arguments of the fit
-    method should be directly passed as Fortran-contiguous numpy arrays.
     """
 
     path = staticmethod(lasso_path)
