MAINT Parameters validation for sklearn.metrics.cluster.homogeneity_completeness_v_measure (#26137)

Jessicakk0711 · jeremiedbb · web-flow · commit 861a759f2c52 · 2023-04-12T16:32:37.000+02:00
Co-authored-by: Jérémie du Boisberranger &lt;34657725+jeremiedbb@users.noreply.github.com&gt;
diff --git a/sklearn/metrics/cluster/_supervised.py b/sklearn/metrics/cluster/_supervised.py
@@ -433,6 +433,13 @@ def adjusted_rand_score(labels_true, labels_pred):
     return 2.0 * (tp * tn - fn * fp) / ((tp + fn) * (fn + tn) + (tp + fp) * (fp + tn))
 
 
+@validate_params(
+    {
+        "labels_true": ["array-like"],
+        "labels_pred": ["array-like"],
+        "beta": [Interval(Real, 0, None, closed="left")],
+    }
+)
 def homogeneity_completeness_v_measure(labels_true, labels_pred, *, beta=1.0):
     """Compute the homogeneity and completeness and V-Measure scores at once.
 
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
@@ -174,6 +174,7 @@ def _check_function_param_validation(
     "sklearn.metrics.cluster.adjusted_mutual_info_score",
     "sklearn.metrics.cluster.contingency_matrix",
     "sklearn.metrics.cluster.fowlkes_mallows_score",
+    "sklearn.metrics.cluster.homogeneity_completeness_v_measure",
     "sklearn.metrics.cluster.normalized_mutual_info_score",
     "sklearn.metrics.cluster.silhouette_samples",
     "sklearn.metrics.cluster.silhouette_score",
