Merge branch 'scikit-learn-contrib:master' into master

Author: adamzenith

README.rst

@@ -203,10 +203,10 @@ For more information on the contribution process, please go `here <CONTRIBUTING.
 🤝  Affiliations
 ================
 
-MAPIE has been developed through a collaboration between Quantmetry, Michelin, and ENS Paris-Saclay
-with the financial support from Région Ile de France.
+MAPIE has been developed through a collaboration between Quantmetry, Michelin, ENS Paris-Saclay,
+Confiance.ai and with the financial support from Région Ile de France.
 
-|Quantmetry|_ |Michelin|_ |ENS|_ |IledeFrance|_ 
+|Quantmetry|_ |Michelin|_ |ENS|_ |Confiance.ai|_  |IledeFrance|_ 
 
 .. |Quantmetry| image:: https://www.quantmetry.com/wp-content/uploads/2020/08/08-Logo-quant-Texte-noir.svg
     :width: 150
@@ -220,6 +220,10 @@ with the financial support from Région Ile de France.
     :width: 100
 .. _ENS: https://ens-paris-saclay.fr/en
 
+.. |Confiance.ai| image:: https://pbs.twimg.com/profile_images/1443838558549258264/EvWlv1Vq_400x400.jpg
+    :width: 100
+.. _Confiance.ai: https://www.confiance.ai/
+
 .. |IledeFrance| image:: https://www.iledefrance.fr/themes/custom/portail_idf/logo.svg
     :width: 100
 .. _IledeFrance: https://www.iledefrance.fr/

mapie/quantile_regression.py

@@ -131,7 +131,7 @@ class MapieQuantileRegressor(MapieRegressor):
         },
         "HistGradientBoostingRegressor": {
             "loss_name": "loss",
-            "alpha_name": "alpha"
+            "alpha_name": "quantile"
         },
         "LGBMRegressor": {
             "loss_name": "objective",

mapie/tests/test_utils.py

@@ -298,3 +298,23 @@ def test_compute_quantiles_2D_and_3D(alphas: NDArray):
     quantiles2 = compute_quantiles(vector2, alphas)
 
     assert (quantiles1 == quantiles2).all()
+
+
+@pytest.mark.parametrize("estimator", [-1, 3, 0.2])
+def test_quantile_prefit_non_iterable(estimator: Any) -> None:
+    """
+    Test that there is a list of estimators provided when cv='prefit'
+    is called for MapieQuantileRegressor.
+    """
+    with pytest.raises(
+        ValueError,
+        match=r".*Estimator for prefit must be an iterable object.*",
+    ):
+        mapie_reg = MapieQuantileRegressor(
+            estimator=estimator,
+            cv="prefit"
+        )
+        mapie_reg.fit(
+            [1, 2, 3],
+            [4, 5, 6]
+        )