Add random state to MapieQuantileRegressor constructor

AUTHORS.rst

@@ -40,5 +40,6 @@ Contributors
 * Pierre de Fréminville <pidefrem>
 * Ambros Marzetta <ambrosm>
 * Carl McBride Ellis <Carl-McBride-Ellis>
+* Tiago Leon Melo <[email protected]>
 * Baptiste Calot <[email protected]>
 To be continued ...

HISTORY.rst

@@ -60,6 +60,7 @@ History
 * Add possibility of passing fit parameters used by estimators.
 * Fix memory issue CQR when testing for upper and lower bounds.
 * Add Winkler Interval Score.
+* Allow `random_state` to be passed when instancing a MapieQuantileRegressor
 
 0.8.2 (2024-01-11)
 ------------------

mapie/regression/quantile_regression.py

@@ -154,10 +154,12 @@ def __init__(
         method: str = "quantile",
         cv: Optional[str] = None,
         alpha: float = 0.1,
+        random_state: Optional[Union[int, np.random.RandomState]] = None,
     ) -> None:
         super().__init__(
             estimator=estimator,
             method=method,
+            random_state=random_state
         )
         self.cv = cv
         self.alpha = alpha
@@ -519,6 +521,7 @@ def fit(
             Controls the shuffling applied to the data before applying the
             split.
             Pass an int for reproducible output across multiple function calls.
+            Overrides random state used in constructor.
             See :term:`Glossary <random_state>`.
 
             By default ``None``.
@@ -571,7 +574,7 @@ def fit(
             checked_estimator = self._check_estimator(self.estimator)
             alpha = self._check_alpha(self.alpha)
             X, y = indexable(X, y)
-            random_state = check_random_state(random_state)
+            random_state = check_random_state(random_state or self.random_state)
             results = self._check_calib_set(
                 X,
                 y,

mapie/tests/test_quantile_regression.py

@@ -791,3 +791,17 @@ def early_stopping_monitor(i, est, locals):
 
     for estimator in mapie.estimators_:
         assert estimator.estimators_.shape[0] == 3
+
+def test_random_state_is_set() -> None:
+    """
+    Test that the same result is obtained if the random state
+    is provided through constructor or through fit()
+    """
+    mapie = MapieQuantileRegressor()
+    mapie_rand = MapieQuantileRegressor(random_state=random_state)
+    mapie.fit(X, y, calib_size=0.5, random_state=random_state)
+    mapie_rand.fit(X, y, calib_size=0.5)
+    y_pred, y_pis = mapie.predict(X)
+    y_pred_rand, y_pis_rand = mapie_rand.predict(X)
+    np.testing.assert_allclose(y_pred, y_pred_rand, rtol=1e-2)
+    np.testing.assert_allclose(y_pis, y_pis_rand, rtol=1e-2)