REFACTOR: remove random_state from EnsembleRegressor (not used) (#597)

Author: Valentin-Laurent

mapie/estimator/regressor.py

@@ -125,12 +125,6 @@ class EnsembleRegressor:
 
         By default ``0``.
 
-    random_state: Optional[Union[int, RandomState]]
-        Pseudo random number generator state used for random sampling.
-        Pass an int for reproducible output across multiple function calls.
-
-        By default ``None``.
-
     Attributes
     ----------
     single_estimator_: sklearn.RegressorMixin
@@ -161,7 +155,6 @@ def __init__(
         cv: Optional[Union[int, str, BaseCrossValidator]],
         agg_function: Optional[str],
         n_jobs: Optional[int],
-        random_state: Optional[Union[int, np.random.RandomState]],
         test_size: Optional[Union[int, float]],
         verbose: int
     ):
@@ -170,7 +163,6 @@ def __init__(
         self.cv = cv
         self.agg_function = agg_function
         self.n_jobs = n_jobs
-        self.random_state = random_state
         self.test_size = test_size
         self.verbose = verbose
 

mapie/regression/regression.py

@@ -549,7 +549,6 @@ def init_fit(
             cv,
             agg_function,
             self.n_jobs,
-            self.random_state,
             self.test_size,
             self.verbose
         )

mapie/tests/test_common.py

@@ -310,7 +310,6 @@ def test_warning_when_import_from_estimator():
             cv=3,
             agg_function="mean",
             n_jobs=1,
-            random_state=0,
             test_size=0.2,
             verbose=0,
         )

mapie/tests/test_regression.py

@@ -751,7 +751,6 @@ def test_aggregate_with_mask_with_invalid_agg_function() -> None:
         KFold(n_splits=5, random_state=None, shuffle=True),
         "nonsense",
         None,
-        random_state,
         0.20,
         False
     )
@@ -1032,7 +1031,6 @@ def test_deprecated_ensemble_regressor_fit_warning() -> None:
         KFold(n_splits=5, random_state=None, shuffle=True),
         "nonsense",
         None,
-        random_state,
         0.20,
         False
     )