scikit-learn
diff --git a/‎sklearn/metrics/_classification.py‎
Lines changed: 16 additions & 1 deletion b/‎sklearn/metrics/_classification.py‎
Lines changed: 16 additions & 1 deletion
diff --git a/‎sklearn/tests/test_public_functions.py‎
Lines changed: 1 addition & 0 deletions b/‎sklearn/tests/test_public_functions.py‎
Lines changed: 1 addition & 0 deletions
@@ -2350,6 +2350,21 @@ def balanced_accuracy_score(y_true, y_pred, *, sample_weight=None, adjusted=Fals
     return score
 
 
+@validate_params(
+    {
+        "y_true": ["array-like", "sparse matrix"],
+        "y_pred": ["array-like", "sparse matrix"],
+        "labels": ["array-like", None],
+        "target_names": ["array-like", None],
+        "sample_weight": ["array-like", None],
+        "digits": [Interval(Integral, 0, None, closed="left")],
+        "output_dict": ["boolean"],
+        "zero_division": [
+            Options(Real, {0, 1}),
+            StrOptions({"warn"}),
+        ],
+    }
+)
 def classification_report(
     y_true,
     y_pred,
@@ -2376,7 +2391,7 @@ def classification_report(
     labels : array-like of shape (n_labels,), default=None
         Optional list of label indices to include in the report.
 
-    target_names : list of str of shape (n_labels,), default=None
+    target_names : array-like of shape (n_labels,), default=None
         Optional display names matching the labels (same order).
 
     sample_weight : array-like of shape (n_samples,), default=None
 
@@ -151,6 +151,7 @@ def _check_function_param_validation(
     "sklearn.metrics.balanced_accuracy_score",
     "sklearn.metrics.brier_score_loss",
     "sklearn.metrics.class_likelihood_ratios",
+    "sklearn.metrics.classification_report",
     "sklearn.metrics.cluster.contingency_matrix",
     "sklearn.metrics.cohen_kappa_score",
     "sklearn.metrics.confusion_matrix",