MAINT Parameters validation for datasets.make_regression (scikit-learn#25899)

Co-authored-by: Jérémie du Boisberranger <[email protected]>

Author: Théophile Baranger

sklearn/datasets/_samples_generator.py

@@ -523,6 +523,21 @@ def make_hastie_10_2(n_samples=12000, *, random_state=None):
     return X, y
 
 
+@validate_params(
+    {
+        "n_samples": [Interval(Integral, 1, None, closed="left")],
+        "n_features": [Interval(Integral, 1, None, closed="left")],
+        "n_informative": [Interval(Integral, 0, None, closed="left")],
+        "n_targets": [Interval(Integral, 1, None, closed="left")],
+        "bias": [Interval(Real, None, None, closed="neither")],
+        "effective_rank": [Interval(Integral, 1, None, closed="left"), None],
+        "tail_strength": [Interval(Real, 0, 1, closed="both")],
+        "noise": [Interval(Real, 0, None, closed="left")],
+        "shuffle": ["boolean"],
+        "coef": ["boolean"],
+        "random_state": ["random_state"],
+    }
+)
 def make_regression(
     n_samples=100,
     n_features=100,

sklearn/tests/test_public_functions.py

@@ -133,6 +133,7 @@ def _check_function_param_validation(
     "sklearn.datasets.make_classification",
     "sklearn.datasets.make_friedman1",
     "sklearn.datasets.make_low_rank_matrix",
+    "sklearn.datasets.make_regression",
     "sklearn.datasets.make_sparse_coded_signal",
     "sklearn.decomposition.sparse_encode",
     "sklearn.feature_extraction.grid_to_graph",