FIX pos_label constraint in roc_curve (param validation) (scikit-learn#25131)

jeremiedbb · web-flow · commit 929b3dc188d8 · 2022-12-07T17:58:39.000+01:00
diff --git a/sklearn/metrics/_ranking.py b/sklearn/metrics/_ranking.py
@@ -21,7 +21,7 @@
 
 import warnings
 from functools import partial
-from numbers import Integral
+from numbers import Real
 
 import numpy as np
 from scipy.sparse import csr_matrix, issparse
@@ -723,7 +723,7 @@ def _binary_clf_curve(y_true, y_score, pos_label=None, sample_weight=None):
     y_score : ndarray of shape (n_samples,)
         Estimated probabilities or output of a decision function.
 
-    pos_label : int or str, default=None
+    pos_label : int, float, bool or str, default=None
         The label of the positive class.
 
     sample_weight : array-like of shape (n_samples,), default=None
@@ -908,7 +908,7 @@ def precision_recall_curve(y_true, probas_pred, *, pos_label=None, sample_weight
     {
         "y_true": ["array-like"],
         "y_score": ["array-like"],
-        "pos_label": [Integral, str, None],
+        "pos_label": [Real, str, "boolean", None],
         "sample_weight": ["array-like", None],
         "drop_intermediate": ["boolean"],
     }
@@ -933,7 +933,7 @@ def roc_curve(
         class, confidence values, or non-thresholded measure of decisions
         (as returned by "decision_function" on some classifiers).
 
-    pos_label : int or str, default=None
+    pos_label : int, float, bool or str, default=None
         The label of the positive class.
         When ``pos_label=None``, if `y_true` is in {-1, 1} or {0, 1},
         ``pos_label`` is set to 1, otherwise an error will be raised.
