diff --git a/sklearn/datasets/_samples_generator.py b/sklearn/datasets/_samples_generator.py
index 59c32125b6ff3..ffe81d9c13a18 100644
--- a/sklearn/datasets/_samples_generator.py
+++ b/sklearn/datasets/_samples_generator.py
@@ -6,7 +6,7 @@
 #          G. Louppe, J. Nothman
 # License: BSD 3 clause
 
-from numbers import Integral
+from numbers import Integral, Real
 import numbers
 import array
 import warnings
@@ -39,6 +39,25 @@ def _generate_hypercube(samples, dimensions, rng):
     return out
 
 
+@validate_params(
+    {
+        "n_samples": [Interval(Integral, 1, None, closed="left")],
+        "n_features": [Interval(Integral, 1, None, closed="left")],
+        "n_informative": [Interval(Integral, 1, None, closed="left")],
+        "n_redundant": [Interval(Integral, 0, None, closed="left")],
+        "n_repeated": [Interval(Integral, 0, None, closed="left")],
+        "n_classes": [Interval(Integral, 1, None, closed="left")],
+        "n_clusters_per_class": [Interval(Integral, 1, None, closed="left")],
+        "weights": ["array-like", None],
+        "flip_y": [Interval(Real, 0, 1, closed="both")],
+        "class_sep": [Interval(Real, 0, None, closed="neither")],
+        "hypercube": ["boolean"],
+        "shift": [Interval(Real, None, None, closed="neither"), "array-like", None],
+        "scale": [Interval(Real, 0, None, closed="neither"), "array-like", None],
+        "shuffle": ["boolean"],
+        "random_state": ["random_state"],
+    }
+)
 def make_classification(
     n_samples=100,
     n_features=20,
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
index 0e95f359a71aa..4a733b1b71252 100644
--- a/sklearn/tests/test_public_functions.py
+++ b/sklearn/tests/test_public_functions.py
@@ -103,6 +103,7 @@ def _check_function_param_validation(
     "sklearn.covariance.empirical_covariance",
     "sklearn.covariance.shrunk_covariance",
     "sklearn.datasets.fetch_california_housing",
+    "sklearn.datasets.make_classification",
     "sklearn.datasets.make_sparse_coded_signal",
     "sklearn.decomposition.sparse_encode",
     "sklearn.feature_extraction.grid_to_graph",