MAINT Parameters validation for metrics.mean_absolute_percentage_error (scikit-learn#25695)

sortofamudkip · web-flow · commit 5bb85454c56e · 2023-02-27T11:14:41.000+01:00
diff --git a/sklearn/metrics/_regression.py b/sklearn/metrics/_regression.py
@@ -305,6 +305,14 @@ def mean_pinball_loss(
     return np.average(output_errors, weights=multioutput)
 
 
+@validate_params(
+    {
+        "y_true": ["array-like"],
+        "y_pred": ["array-like"],
+        "sample_weight": ["array-like", None],
+        "multioutput": [StrOptions({"raw_values", "uniform_average"}), "array-like"],
+    }
+)
 def mean_absolute_percentage_error(
     y_true, y_pred, *, sample_weight=None, multioutput="uniform_average"
 ):
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
@@ -127,6 +127,7 @@ def _check_function_param_validation(
     "sklearn.metrics.log_loss",
     "sklearn.metrics.max_error",
     "sklearn.metrics.mean_absolute_error",
+    "sklearn.metrics.mean_absolute_percentage_error",
     "sklearn.metrics.mean_pinball_loss",
     "sklearn.metrics.mean_squared_error",
     "sklearn.metrics.mean_tweedie_deviance",
