MAINT Parameters validation for sklearn.metrics.f1_score (#25557)

nwzish · jeremiedbb · web-flow · commit 7970d78cfc1f · 2023-02-08T20:54:06.000+01:00
Co-authored-by: Jérémie du Boisberranger &lt;34657725+jeremiedbb@users.noreply.github.com&gt;
diff --git a/sklearn/metrics/_classification.py b/sklearn/metrics/_classification.py
@@ -23,6 +23,7 @@
 # License: BSD 3 clause
 
 
+from numbers import Integral, Real
 import warnings
 import numpy as np
 
@@ -40,7 +41,7 @@
 from ..utils.multiclass import type_of_target
 from ..utils.validation import _num_samples
 from ..utils.sparsefuncs import count_nonzero
-from ..utils._param_validation import StrOptions, validate_params
+from ..utils._param_validation import StrOptions, Options, validate_params
 from ..exceptions import UndefinedMetricWarning
 
 from ._base import _check_pos_label_consistency
@@ -1038,6 +1039,23 @@ def zero_one_loss(y_true, y_pred, *, normalize=True, sample_weight=None):
         return n_samples - score
 
 
+@validate_params(
+    {
+        "y_true": ["array-like", "sparse matrix"],
+        "y_pred": ["array-like", "sparse matrix"],
+        "labels": ["array-like", None],
+        "pos_label": [Real, str, "boolean", None],
+        "average": [
+            StrOptions({"micro", "macro", "samples", "weighted", "binary"}),
+            None,
+        ],
+        "sample_weight": ["array-like", None],
+        "zero_division": [
+            Options(Integral, {0, 1}),
+            StrOptions({"warn"}),
+        ],
+    }
+)
 def f1_score(
     y_true,
     y_pred,
@@ -1083,7 +1101,7 @@ def f1_score(
         .. versionchanged:: 0.17
            Parameter `labels` improved for multiclass problem.
 
-    pos_label : int, float, bool or str, default=1
+    pos_label : int, float, bool, str or None, default=1
         The class to report if ``average='binary'`` and the data is binary.
         If the data are multiclass or multilabel, this will be ignored;
         setting ``labels=[pos_label]`` and ``average != 'binary'`` will report
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
@@ -120,6 +120,7 @@ def _check_function_param_validation(
     "sklearn.metrics.confusion_matrix",
     "sklearn.metrics.d2_pinball_score",
     "sklearn.metrics.det_curve",
+    "sklearn.metrics.f1_score",
     "sklearn.metrics.hamming_loss",
     "sklearn.metrics.mean_absolute_error",
     "sklearn.metrics.mean_squared_error",
