DOC Add missing directives to det_curve-related docstrings (scikit-learn#31225)

Co-authored-by: ArturoAmorQ <[email protected]>

Author: ArturoAmorQ

sklearn/metrics/_plot/det_curve.py

@@ -120,6 +120,8 @@ def from_estimator(
             from the previous or subsequent threshold. All points with the same
             tp value have the same `fnr` and thus same y coordinate.
 
+            .. versionadded:: 1.7
+
         response_method : {'predict_proba', 'decision_function', 'auto'} \
                 default='auto'
             Specifies whether to use :term:`predict_proba` or
@@ -227,6 +229,8 @@ def from_predictions(
             from the previous or subsequent threshold. All points with the same
             tp value have the same `fnr` and thus same y coordinate.
 
+            .. versionadded:: 1.7
+
         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

sklearn/metrics/_ranking.py

@@ -334,8 +334,11 @@ def det_curve(
 
     thresholds : ndarray of shape (n_thresholds,)
         Decreasing thresholds on the decision function (either `predict_proba`
-        or `decision_function`) used to compute FPR and FNR. An arbitrary
-        threshold at infinity is added for the case `fpr=0` and `fnr=1`.
+        or `decision_function`) used to compute FPR and FNR.
+
+        .. versionchanged:: 1.7
+           An arbitrary threshold at infinity is added for the case `fpr=0`
+           and `fnr=1`.
 
     See Also
     --------