From d098d1223e09777da8ce379647152653cedf574c Mon Sep 17 00:00:00 2001
From: Bagus Tris Atmaja <bagustris@outlook.com>
Date: Tue, 17 Sep 2024 12:10:46 +0900
Subject: [PATCH 01/14] REFAC update ROC curve plotting to use y_score instead
 of y_pred; deprecate y_pred

---
 sklearn/metrics/_plot/roc_curve.py | 38 +++++++++++++++++++++++-------
 sklearn/metrics/_ranking.py        |  8 +++----
 2 files changed, 34 insertions(+), 12 deletions(-)

diff --git a/sklearn/metrics/_plot/roc_curve.py b/sklearn/metrics/_plot/roc_curve.py
index e9d4ca5d5672d..8ff745115bb5a 100644
--- a/sklearn/metrics/_plot/roc_curve.py
+++ b/sklearn/metrics/_plot/roc_curve.py
@@ -1,6 +1,7 @@
 # Authors: The scikit-learn developers
 # SPDX-License-Identifier: BSD-3-Clause
 
+import warnings
 from ...utils._plotting import _BinaryClassifierCurveDisplayMixin
 from .._ranking import auc, roc_curve
 
@@ -275,7 +276,7 @@ def from_estimator(
         <...>
         >>> plt.show()
         """
-        y_pred, pos_label, name = cls._validate_and_get_response_values(
+        y_score, pos_label, name = cls._validate_and_get_response_values(
             estimator,
             X,
             y,
@@ -286,7 +287,7 @@ def from_estimator(
 
         return cls.from_predictions(
             y_true=y,
-            y_pred=y_pred,
+            y_score=y_score,
             sample_weight=sample_weight,
             drop_intermediate=drop_intermediate,
             name=name,
@@ -301,7 +302,7 @@ def from_estimator(
     def from_predictions(
         cls,
         y_true,
-        y_pred,
+        y_score,
         *,
         sample_weight=None,
         drop_intermediate=True,
@@ -310,6 +311,7 @@ def from_predictions(
         ax=None,
         plot_chance_level=False,
         chance_level_kw=None,
+        y_pred="deprecated",
         **kwargs,
     ):
         """Plot ROC curve given the true and predicted values.
@@ -323,11 +325,15 @@ def from_predictions(
         y_true : array-like of shape (n_samples,)
             True labels.
 
-        y_pred : array-like of shape (n_samples,)
+        y_score : array-like of shape (n_samples,)
             Target scores, can either be probability estimates of the positive
             class, confidence values, or non-thresholded measure of decisions
             (as returned by “decision_function” on some classifiers).
 
+            .. deprecated:: 1.6
+                `y_pred` is deprecated and will be removed in 1.8. Use
+                `y_score` instead.
+ 
         sample_weight : array-like of shape (n_samples,), default=None
             Sample weights.
 
@@ -386,19 +392,35 @@ def from_predictions(
         >>> X_train, X_test, y_train, y_test = train_test_split(
         ...     X, y, random_state=0)
         >>> clf = SVC(random_state=0).fit(X_train, y_train)
-        >>> y_pred = clf.decision_function(X_test)
+        >>> y_score = clf.decision_function(X_test)
         >>> RocCurveDisplay.from_predictions(
-        ...    y_test, y_pred)
+        ...    y_test, y_score)
         <...>
         >>> plt.show()
         """
+        # TODO(1.8): Remove y_pred support and use y_score only
+        if y_score is not None and not isinstance(y_pred, str):
+            raise ValueError(
+                "`y_pred` and `y_score` cannot be both specified. Please use `y_score`"
+                " only as `y_pred` is deprecated in v1.6 and will be removed in v1.8."
+            )
+        if y_score is None:
+            warnings.warn(
+                (
+                    "y_pred was deprecated in version 1.6 and will be removed in 1.8. "
+                    "Please use ``y_score`` instead."
+                ),
+                FutureWarning,
+            )
+            y_score = y_pred
+        
         pos_label_validated, name = cls._validate_from_predictions_params(
-            y_true, y_pred, sample_weight=sample_weight, pos_label=pos_label, name=name
+            y_true, y_score, sample_weight=sample_weight, pos_label=pos_label, name=name
         )
 
         fpr, tpr, _ = roc_curve(
             y_true,
-            y_pred,
+            y_score,
             pos_label=pos_label,
             sample_weight=sample_weight,
             drop_intermediate=drop_intermediate,
diff --git a/sklearn/metrics/_ranking.py b/sklearn/metrics/_ranking.py
index fd5c30805a0c0..5b2f707bcc153 100644
--- a/sklearn/metrics/_ranking.py
+++ b/sklearn/metrics/_ranking.py
@@ -73,9 +73,9 @@ def auc(x, y):
     --------
     >>> import numpy as np
     >>> from sklearn import metrics
-    >>> y = np.array([1, 1, 2, 2])
-    >>> pred = np.array([0.1, 0.4, 0.35, 0.8])
-    >>> fpr, tpr, thresholds = metrics.roc_curve(y, pred, pos_label=2)
+    >>> y_true = np.array([1, 1, 2, 2])
+    >>> y_score = np.array([0.1, 0.4, 0.35, 0.8])
+    >>> fpr, tpr, thresholds = metrics.roc_curve(y_true, y_score, pos_label=2)
     >>> metrics.auc(fpr, tpr)
     np.float64(0.75)
     """
@@ -985,7 +985,7 @@ def precision_recall_curve(
         warnings.warn(
             (
                 "probas_pred was deprecated in version 1.5 and will be removed in 1.7."
-                "Please use ``y_score`` instead."
+                "Please use `y_score` instead."
             ),
             FutureWarning,
         )

From cb2836690481592ca86c3b096bf078da5e5b4c82 Mon Sep 17 00:00:00 2001
From: Bagus Tris Atmaja <bagustris@outlook.com>
Date: Fri, 20 Sep 2024 11:18:00 +0900
Subject: [PATCH 02/14] change y_pred to y_score in roc_curve.py

---
 doc/whats_new/v1.6.rst             |  2 ++
 sklearn/metrics/_plot/roc_curve.py | 10 +++++-----
 sklearn/metrics/_ranking.py        |  6 +++---
 3 files changed, 10 insertions(+), 8 deletions(-)

diff --git a/doc/whats_new/v1.6.rst b/doc/whats_new/v1.6.rst
index 22a0d7acfd24e..b8792d7080571 100644
--- a/doc/whats_new/v1.6.rst
+++ b/doc/whats_new/v1.6.rst
@@ -277,6 +277,8 @@ Changelog
 :mod:`sklearn.metrics`
 ......................
 
+- |API| In :func:`sklearn.metrics.roc_curve`, the argument `y_pred` has been renamed to `y_score` to better reflect its purpose. `y_pred` will be removed in 1.8. :pr:`29865` by :user:`Bagus Tris Atmaja <bagustris>`.
+
 - |Enhancement| :func:`sklearn.metrics.check_scoring` now accepts `raise_exc` to specify
   whether to raise an exception if a subset of the scorers in multimetric scoring fails
   or to return an error code. :pr:`28992` by :user:`Stefanie Senger <StefanieSenger>`.
diff --git a/sklearn/metrics/_plot/roc_curve.py b/sklearn/metrics/_plot/roc_curve.py
index 8ff745115bb5a..342cde1b66432 100644
--- a/sklearn/metrics/_plot/roc_curve.py
+++ b/sklearn/metrics/_plot/roc_curve.py
@@ -68,9 +68,9 @@ class RocCurveDisplay(_BinaryClassifierCurveDisplayMixin):
     >>> import matplotlib.pyplot as plt
     >>> import numpy as np
     >>> from sklearn import metrics
-    >>> y = np.array([0, 0, 1, 1])
-    >>> pred = np.array([0.1, 0.4, 0.35, 0.8])
-    >>> fpr, tpr, thresholds = metrics.roc_curve(y, pred)
+    >>> y_true = np.array([0, 0, 1, 1])
+    >>> y_score = np.array([0.1, 0.4, 0.35, 0.8])
+    >>> fpr, tpr, thresholds = metrics.roc_curve(y_true, y_score)
     >>> roc_auc = metrics.auc(fpr, tpr)
     >>> display = metrics.RocCurveDisplay(fpr=fpr, tpr=tpr, roc_auc=roc_auc,
     ...                                   estimator_name='example estimator')
@@ -333,7 +333,7 @@ def from_predictions(
             .. deprecated:: 1.6
                 `y_pred` is deprecated and will be removed in 1.8. Use
                 `y_score` instead.
- 
+
         sample_weight : array-like of shape (n_samples,), default=None
             Sample weights.
 
@@ -413,7 +413,7 @@ def from_predictions(
                 FutureWarning,
             )
             y_score = y_pred
-        
+
         pos_label_validated, name = cls._validate_from_predictions_params(
             y_true, y_score, sample_weight=sample_weight, pos_label=pos_label, name=name
         )
diff --git a/sklearn/metrics/_ranking.py b/sklearn/metrics/_ranking.py
index 5b2f707bcc153..dc8e0a4d2cd2e 100644
--- a/sklearn/metrics/_ranking.py
+++ b/sklearn/metrics/_ranking.py
@@ -595,10 +595,10 @@ class scores must correspond to the order of ``labels``,
     >>> clf = MultiOutputClassifier(clf).fit(X, y)
     >>> # get a list of n_output containing probability arrays of shape
     >>> # (n_samples, n_classes)
-    >>> y_pred = clf.predict_proba(X)
+    >>> y_score = clf.predict_proba(X)
     >>> # extract the positive columns for each output
-    >>> y_pred = np.transpose([pred[:, 1] for pred in y_pred])
-    >>> roc_auc_score(y, y_pred, average=None)
+    >>> y_score = np.transpose([score[:, 1] for score in y_score])
+    >>> roc_auc_score(y, y_score, average=None)
     array([0.82..., 0.86..., 0.94..., 0.85... , 0.94...])
     >>> from sklearn.linear_model import RidgeClassifierCV
     >>> clf = RidgeClassifierCV().fit(X, y)

From 67b15b7f7cc26dd9c9f0caaa03f59419ae540af2 Mon Sep 17 00:00:00 2001
From: Bagus Tris Atmaja <bagustris@outlook.com>
Date: Fri, 20 Sep 2024 11:23:49 +0900
Subject: [PATCH 03/14] 	modified:   sklearn/metrics/_plot/roc_curve.py

---
 sklearn/metrics/_plot/roc_curve.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/sklearn/metrics/_plot/roc_curve.py b/sklearn/metrics/_plot/roc_curve.py
index 342cde1b66432..4f90518d6db87 100644
--- a/sklearn/metrics/_plot/roc_curve.py
+++ b/sklearn/metrics/_plot/roc_curve.py
@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: BSD-3-Clause
 
 import warnings
+
 from ...utils._plotting import _BinaryClassifierCurveDisplayMixin
 from .._ranking import auc, roc_curve
 

From 55e172031a2055a18273009203b79e67a848706f Mon Sep 17 00:00:00 2001
From: Bagus Tris Atmaja <bagustris@outlook.com>
Date: Tue, 24 Sep 2024 17:03:03 +0900
Subject: [PATCH 04/14] move what's new, revert warn, add condition to raise
 warning

---
 doc/whats_new/v1.6.rst             |  5 +++--
 sklearn/metrics/_plot/roc_curve.py | 15 ++++++++++-----
 sklearn/metrics/_ranking.py        |  2 +-
 3 files changed, 14 insertions(+), 8 deletions(-)

diff --git a/doc/whats_new/v1.6.rst b/doc/whats_new/v1.6.rst
index b8792d7080571..f9e189f649da1 100644
--- a/doc/whats_new/v1.6.rst
+++ b/doc/whats_new/v1.6.rst
@@ -277,8 +277,6 @@ Changelog
 :mod:`sklearn.metrics`
 ......................
 
-- |API| In :func:`sklearn.metrics.roc_curve`, the argument `y_pred` has been renamed to `y_score` to better reflect its purpose. `y_pred` will be removed in 1.8. :pr:`29865` by :user:`Bagus Tris Atmaja <bagustris>`.
-
 - |Enhancement| :func:`sklearn.metrics.check_scoring` now accepts `raise_exc` to specify
   whether to raise an exception if a subset of the scorers in multimetric scoring fails
   or to return an error code. :pr:`28992` by :user:`Stefanie Senger <StefanieSenger>`.
@@ -301,6 +299,9 @@ Changelog
   is renamed into `ensure_all_finite`. `force_all_finite` will be removed in 1.8.
   :pr:`29404` by :user:`Jérémie du Boisberranger <jeremiedb>`.
 
+- |API| In :func:`sklearn.metrics.RocCurveDisplay.from_predictions`, the argument `y_pred` has been renamed to `y_score` to better reflect its purpose. `y_pred` will be removed in 1.8. 
+  :pr:`29865` by :user:`Bagus Tris Atmaja <bagustris>`.
+
 :mod:`sklearn.model_selection`
 ..............................
 
diff --git a/sklearn/metrics/_plot/roc_curve.py b/sklearn/metrics/_plot/roc_curve.py
index 4f90518d6db87..f7443ae5be34b 100644
--- a/sklearn/metrics/_plot/roc_curve.py
+++ b/sklearn/metrics/_plot/roc_curve.py
@@ -331,10 +331,6 @@ def from_predictions(
             class, confidence values, or non-thresholded measure of decisions
             (as returned by “decision_function” on some classifiers).
 
-            .. deprecated:: 1.6
-                `y_pred` is deprecated and will be removed in 1.8. Use
-                `y_score` instead.
-
         sample_weight : array-like of shape (n_samples,), default=None
             Sample weights.
 
@@ -367,6 +363,15 @@ def from_predictions(
 
             .. versionadded:: 1.3
 
+        y_pred : array-like of shape (n_samples,)
+            Target scores, can either be probability estimates of the positive
+            class, confidence values, or non-thresholded measure of decisions
+            (as returned by “decision_function” on some classifiers).
+
+            .. deprecated:: 1.6
+                `y_pred` is deprecated and will be removed in 1.8. Use
+                `y_score` instead.
+
         **kwargs : dict
             Additional keywords arguments passed to matplotlib `plot` function.
 
@@ -405,7 +410,7 @@ def from_predictions(
                 "`y_pred` and `y_score` cannot be both specified. Please use `y_score`"
                 " only as `y_pred` is deprecated in v1.6 and will be removed in v1.8."
             )
-        if y_score is None:
+        if y_pred is not None and y_pred != "deprecated":
             warnings.warn(
                 (
                     "y_pred was deprecated in version 1.6 and will be removed in 1.8. "
diff --git a/sklearn/metrics/_ranking.py b/sklearn/metrics/_ranking.py
index dc8e0a4d2cd2e..344cd9b077de0 100644
--- a/sklearn/metrics/_ranking.py
+++ b/sklearn/metrics/_ranking.py
@@ -985,7 +985,7 @@ def precision_recall_curve(
         warnings.warn(
             (
                 "probas_pred was deprecated in version 1.5 and will be removed in 1.7."
-                "Please use `y_score` instead."
+                "Please use ``y_score`` instead."
             ),
             FutureWarning,
         )

From 9f154218890dc7e5953e6b6af22e83c9fade2a6c Mon Sep 17 00:00:00 2001
From: Bagus Tris Atmaja <bagustris@outlook.com>
Date: Fri, 11 Oct 2024 10:06:51 +0900
Subject: [PATCH 05/14] add unit test

---
 .../_plot/tests/test_roc_curve_display.py     | 40 +++++++++++++++++++
 1 file changed, 40 insertions(+)

diff --git a/sklearn/metrics/_plot/tests/test_roc_curve_display.py b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
index a4f4d81fb9ded..1f8055dfc0553 100644
--- a/sklearn/metrics/_plot/tests/test_roc_curve_display.py
+++ b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
@@ -13,6 +13,8 @@
 from sklearn.preprocessing import StandardScaler
 from sklearn.utils import shuffle
 
+import warnings
+
 
 @pytest.fixture(scope="module")
 def data():
@@ -313,3 +315,41 @@ def test_plot_roc_curve_pos_label(pyplot, response_method, constructor_name):
 
     assert display.roc_auc == pytest.approx(roc_auc_limit)
     assert trapezoid(display.tpr, display.fpr) == pytest.approx(roc_auc_limit)
+
+
+# TODO(1.8): remove
+def test_y_pred_and_y_score_both_specified():
+    with pytest.raises(
+        ValueError, match="`y_pred` and `y_score` cannot be both specified"
+    ):
+        RocCurveDisplay.from_predictions(
+            y_true=np.array([0, 1, 1, 0]),
+            y_pred=np.array([0.1, 0.4, 0.35, 0.8]),
+            y_score=np.array([0.2, 0.3, 0.5, 0.1]),
+        )
+
+
+def test_y_pred_deprecation_warning():
+    with pytest.warns(FutureWarning, match="y_pred was deprecated in version 1.6"):
+        RocCurveDisplay.from_predictions(
+            y_true=np.array([0, 1, 1, 0]), y_pred=np.array([0.1, 0.4, 0.35, 0.8])
+        )
+
+
+def test_y_pred_deprecated_value():
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        display = RocCurveDisplay.from_predictions(
+            y_true=np.array([0, 1, 1, 0]),
+            y_pred="deprecated",
+            y_score=np.array([0.1, 0.4, 0.35, 0.8]),
+        )
+    assert np.array_equal(display.y_score, np.array([0.1, 0.4, 0.35, 0.8]))
+
+
+def test_y_score_used_when_y_pred_not_specified():
+    y_score = np.array([0.1, 0.4, 0.35, 0.8])
+    display = RocCurveDisplay.from_predictions(
+        y_true=np.array([0, 1, 1, 0]), y_score=y_score
+    )
+    assert np.array_equal(display.y_score, y_score)

From eaeece68bd9a83da6226d5491890ddb5c26f686b Mon Sep 17 00:00:00 2001
From: Bagus Tris Atmaja <bagustris@outlook.com>
Date: Fri, 11 Oct 2024 11:16:50 +0900
Subject: [PATCH 06/14] update and fix unit test

---
 .../_plot/tests/test_roc_curve_display.py     | 69 ++++++++-----------
 1 file changed, 27 insertions(+), 42 deletions(-)

diff --git a/sklearn/metrics/_plot/tests/test_roc_curve_display.py b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
index 1f8055dfc0553..a45b9e3e3591e 100644
--- a/sklearn/metrics/_plot/tests/test_roc_curve_display.py
+++ b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
@@ -13,8 +13,6 @@
 from sklearn.preprocessing import StandardScaler
 from sklearn.utils import shuffle
 
-import warnings
-
 
 @pytest.fixture(scope="module")
 def data():
@@ -65,8 +63,8 @@ def test_roc_curve_display_plotting(
     lr = LogisticRegression()
     lr.fit(X, y)
 
-    y_pred = getattr(lr, response_method)(X)
-    y_pred = y_pred if y_pred.ndim == 1 else y_pred[:, 1]
+    y_score = getattr(lr, response_method)(X)
+    y_score = y_score if y_score.ndim == 1 else y_score[:, 1]
 
     if constructor_name == "from_estimator":
         display = RocCurveDisplay.from_estimator(
@@ -81,7 +79,7 @@ def test_roc_curve_display_plotting(
     else:
         display = RocCurveDisplay.from_predictions(
             y,
-            y_pred,
+            y_score,
             sample_weight=sample_weight,
             drop_intermediate=drop_intermediate,
             pos_label=pos_label,
@@ -90,7 +88,7 @@ def test_roc_curve_display_plotting(
 
     fpr, tpr, _ = roc_curve(
         y,
-        y_pred,
+        y_score,
         sample_weight=sample_weight,
         drop_intermediate=drop_intermediate,
         pos_label=pos_label,
@@ -145,8 +143,8 @@ def test_roc_curve_chance_level_line(
     lr = LogisticRegression()
     lr.fit(X, y)
 
-    y_pred = getattr(lr, "predict_proba")(X)
-    y_pred = y_pred if y_pred.ndim == 1 else y_pred[:, 1]
+    y_score = getattr(lr, "predict_proba")(X)
+    y_score = y_score if y_score.ndim == 1 else y_score[:, 1]
 
     if constructor_name == "from_estimator":
         display = RocCurveDisplay.from_estimator(
@@ -160,7 +158,7 @@ def test_roc_curve_chance_level_line(
     else:
         display = RocCurveDisplay.from_predictions(
             y,
-            y_pred,
+            y_score,
             alpha=0.8,
             plot_chance_level=plot_chance_level,
             chance_level_kw=chance_level_kw,
@@ -272,11 +270,11 @@ def test_plot_roc_curve_pos_label(pyplot, response_method, constructor_name):
     # are betrayed by the class imbalance
     assert classifier.classes_.tolist() == ["cancer", "not cancer"]
 
-    y_pred = getattr(classifier, response_method)(X_test)
+    y_score = getattr(classifier, response_method)(X_test)
     # we select the corresponding probability columns or reverse the decision
     # function otherwise
-    y_pred_cancer = -1 * y_pred if y_pred.ndim == 1 else y_pred[:, 0]
-    y_pred_not_cancer = y_pred if y_pred.ndim == 1 else y_pred[:, 1]
+    y_score_cancer = -1 * y_score if y_score.ndim == 1 else y_score[:, 0]
+    y_score_not_cancer = y_score if y_score.ndim == 1 else y_score[:, 1]
 
     if constructor_name == "from_estimator":
         display = RocCurveDisplay.from_estimator(
@@ -289,7 +287,7 @@ def test_plot_roc_curve_pos_label(pyplot, response_method, constructor_name):
     else:
         display = RocCurveDisplay.from_predictions(
             y_test,
-            y_pred_cancer,
+            y_score_cancer,
             pos_label="cancer",
         )
 
@@ -309,7 +307,7 @@ def test_plot_roc_curve_pos_label(pyplot, response_method, constructor_name):
     else:
         display = RocCurveDisplay.from_predictions(
             y_test,
-            y_pred_not_cancer,
+            y_score_not_cancer,
             pos_label="not cancer",
         )
 
@@ -318,38 +316,25 @@ def test_plot_roc_curve_pos_label(pyplot, response_method, constructor_name):
 
 
 # TODO(1.8): remove
-def test_y_pred_and_y_score_both_specified():
+def test_y_score_and_y_pred_deprecation():
+    y_true = np.array([0, 1, 1, 0])
+    y_score = np.array([0.1, 0.4, 0.35, 0.8])
+    y_pred = np.array([0.2, 0.3, 0.5, 0.1])
+
+    # Test that an error is raised when both y_score and y_pred are specified
     with pytest.raises(
         ValueError, match="`y_pred` and `y_score` cannot be both specified"
     ):
-        RocCurveDisplay.from_predictions(
-            y_true=np.array([0, 1, 1, 0]),
-            y_pred=np.array([0.1, 0.4, 0.35, 0.8]),
-            y_score=np.array([0.2, 0.3, 0.5, 0.1]),
-        )
-
-
-def test_y_pred_deprecation_warning():
-    with pytest.warns(FutureWarning, match="y_pred was deprecated in version 1.6"):
-        RocCurveDisplay.from_predictions(
-            y_true=np.array([0, 1, 1, 0]), y_pred=np.array([0.1, 0.4, 0.35, 0.8])
-        )
-
-
-def test_y_pred_deprecated_value():
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore")
-        display = RocCurveDisplay.from_predictions(
-            y_true=np.array([0, 1, 1, 0]),
-            y_pred="deprecated",
-            y_score=np.array([0.1, 0.4, 0.35, 0.8]),
-        )
-    assert np.array_equal(display.y_score, np.array([0.1, 0.4, 0.35, 0.8]))
+        RocCurveDisplay.from_predictions(y_true, y_score=y_score, y_pred=y_pred)
 
+    # Test that y_score is used when y_pred is not specified
+    display = RocCurveDisplay.from_predictions(y_true, y_score=y_score)
+    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
+    assert_allclose(display.tpr, [0, 0, 1, 1])
 
-def test_y_score_used_when_y_pred_not_specified():
-    y_score = np.array([0.1, 0.4, 0.35, 0.8])
+    # Test that y_score is used when y_pred is "deprecated"
     display = RocCurveDisplay.from_predictions(
-        y_true=np.array([0, 1, 1, 0]), y_score=y_score
+        y_true, y_score=y_score, y_pred="deprecated"
     )
-    assert np.array_equal(display.y_score, y_score)
+    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
+    assert_allclose(display.tpr, [0, 0, 1, 1])

From fd381db4d5826960a12d11a969e7eb4badeace6d Mon Sep 17 00:00:00 2001
From: Bagus Tris Atmaja <bagustris@outlook.com>
Date: Fri, 11 Oct 2024 13:29:20 +0900
Subject: [PATCH 07/14] add test for y_pred depreciation warning

---
 .../_plot/tests/test_roc_curve_display.py     | 20 +++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/sklearn/metrics/_plot/tests/test_roc_curve_display.py b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
index a45b9e3e3591e..2e43a07869c8f 100644
--- a/sklearn/metrics/_plot/tests/test_roc_curve_display.py
+++ b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
@@ -338,3 +338,23 @@ def test_y_score_and_y_pred_deprecation():
     )
     assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
     assert_allclose(display.tpr, [0, 0, 1, 1])
+
+
+def test_y_pred_deprecation_warning():
+    y_true = np.array([0, 1, 1, 0])
+    y_pred = np.array([0.1, 0.4, 0.35, 0.8])
+
+    with pytest.warns(FutureWarning, match="y_pred was deprecated in version 1.6"):
+        display = RocCurveDisplay.from_predictions(y_true, y_pred=y_pred)
+
+    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
+    assert_allclose(display.tpr, [0, 0, 1, 1])
+
+    # Test that y_score is used when y_pred is "deprecated"
+    y_score = np.array([0.2, 0.3, 0.5, 0.1])
+    display = RocCurveDisplay.from_predictions(
+        y_true, y_score=y_score, y_pred="deprecated"
+    )
+    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
+    assert_allclose(display.tpr, [0, 0, 1, 1])
+    assert np.array_equal(display.y_score, y_score)

From 1b402c53f90734e7713571cea54277353e2209e3 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Fri, 11 Oct 2024 17:53:14 +0200
Subject: [PATCH 08/14] remove trailing spaces

---
 doc/whats_new/v1.6.rst | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/doc/whats_new/v1.6.rst b/doc/whats_new/v1.6.rst
index 2349ca464503b..53bed57a01503 100644
--- a/doc/whats_new/v1.6.rst
+++ b/doc/whats_new/v1.6.rst
@@ -316,9 +316,9 @@ Changelog
   is renamed into `ensure_all_finite`. `force_all_finite` will be removed in 1.8.
   :pr:`29404` by :user:`Jérémie du Boisberranger <jeremiedb>`.
 
-- |API| In :func:`sklearn.metrics.RocCurveDisplay.from_predictions`, 
-  the argument `y_pred` has been renamed to `y_score` to better reflect its purpose. 
-  `y_pred` will be removed in 1.8. 
+- |API| In :func:`sklearn.metrics.RocCurveDisplay.from_predictions`,
+  the argument `y_pred` has been renamed to `y_score` to better reflect its purpose.
+  `y_pred` will be removed in 1.8.
   :pr:`29865` by :user:`Bagus Tris Atmaja <bagustris>`.
 
 - |Fix| the functions :func:`metrics.mean_squared_log_error` and
@@ -333,8 +333,6 @@ Changelog
   will be returned when `multioutput=uniform_average`.
   :pr:`29709` by :user:`Virgil Chan <virchan>`.
 
-
-
 :mod:`sklearn.model_selection`
 ..............................
 

From 389aa8ee275e81b105e490866713392eef4375bb Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 2 Jan 2025 13:43:30 +0100
Subject: [PATCH 09/14] fix

---
 sklearn/metrics/_plot/roc_curve.py | 26 +++++++++++++++-----------
 1 file changed, 15 insertions(+), 11 deletions(-)

diff --git a/sklearn/metrics/_plot/roc_curve.py b/sklearn/metrics/_plot/roc_curve.py
index f7443ae5be34b..6042639f8c5fe 100644
--- a/sklearn/metrics/_plot/roc_curve.py
+++ b/sklearn/metrics/_plot/roc_curve.py
@@ -303,7 +303,7 @@ def from_estimator(
     def from_predictions(
         cls,
         y_true,
-        y_score,
+        y_score=None,
         *,
         sample_weight=None,
         drop_intermediate=True,
@@ -331,6 +331,9 @@ def from_predictions(
             class, confidence values, or non-thresholded measure of decisions
             (as returned by “decision_function” on some classifiers).
 
+            .. versionadded:: 1.7
+                `y_score` is now used instead of `y_pred`.
+
         sample_weight : array-like of shape (n_samples,), default=None
             Sample weights.
 
@@ -368,8 +371,8 @@ def from_predictions(
             class, confidence values, or non-thresholded measure of decisions
             (as returned by “decision_function” on some classifiers).
 
-            .. deprecated:: 1.6
-                `y_pred` is deprecated and will be removed in 1.8. Use
+            .. deprecated:: 1.7
+                `y_pred` is deprecated and will be removed in 1.9. Use
                 `y_score` instead.
 
         **kwargs : dict
@@ -399,22 +402,23 @@ def from_predictions(
         ...     X, y, random_state=0)
         >>> clf = SVC(random_state=0).fit(X_train, y_train)
         >>> y_score = clf.decision_function(X_test)
-        >>> RocCurveDisplay.from_predictions(
-        ...    y_test, y_score)
+        >>> RocCurveDisplay.from_predictions(y_test, y_score)
         <...>
         >>> plt.show()
         """
-        # TODO(1.8): Remove y_pred support and use y_score only
-        if y_score is not None and not isinstance(y_pred, str):
+        # TODO(1.8): remove after the end of the deprecation period of `y_pred`
+        if y_score is not None and (
+            not isinstance(y_pred, str) or y_pred != "deprecated"
+        ):
             raise ValueError(
                 "`y_pred` and `y_score` cannot be both specified. Please use `y_score`"
-                " only as `y_pred` is deprecated in v1.6 and will be removed in v1.8."
+                " only as `y_pred` is deprecated in 1.7 and will be removed in 1.9."
             )
-        if y_pred is not None and y_pred != "deprecated":
+        if not isinstance(y_pred, str) or y_pred != "deprecated":
             warnings.warn(
                 (
-                    "y_pred was deprecated in version 1.6 and will be removed in 1.8. "
-                    "Please use ``y_score`` instead."
+                    "y_pred is deprecated in 1.7 and will be removed in 1.9. "
+                    "Please use `y_score` instead."
                 ),
                 FutureWarning,
             )

From b0b7b70300abcc9cae4e4b15d90462b3c2b4a05b Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 2 Jan 2025 14:28:34 +0100
Subject: [PATCH 10/14] fix test

---
 .../_plot/tests/test_roc_curve_display.py     | 41 ++++++-------------
 1 file changed, 13 insertions(+), 28 deletions(-)

diff --git a/sklearn/metrics/_plot/tests/test_roc_curve_display.py b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
index 7d3f54494e0f2..8f6e12b54f5f8 100644
--- a/sklearn/metrics/_plot/tests/test_roc_curve_display.py
+++ b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
@@ -336,49 +336,34 @@ def test_plot_roc_curve_pos_label(pyplot, response_method, constructor_name):
     assert trapezoid(display.tpr, display.fpr) == pytest.approx(roc_auc_limit)
 
 
-# TODO(1.8): remove
-def test_y_score_and_y_pred_deprecation():
+# TODO(1.9): remove
+def test_y_score_and_y_pred_specified_error():
+    """Check that an error is raised when both y_score and y_pred are specified."""
     y_true = np.array([0, 1, 1, 0])
     y_score = np.array([0.1, 0.4, 0.35, 0.8])
     y_pred = np.array([0.2, 0.3, 0.5, 0.1])
 
-    # Test that an error is raised when both y_score and y_pred are specified
     with pytest.raises(
         ValueError, match="`y_pred` and `y_score` cannot be both specified"
     ):
         RocCurveDisplay.from_predictions(y_true, y_score=y_score, y_pred=y_pred)
 
-    # Test that y_score is used when y_pred is not specified
-    display = RocCurveDisplay.from_predictions(y_true, y_score=y_score)
-    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
-    assert_allclose(display.tpr, [0, 0, 1, 1])
-
-    # Test that y_score is used when y_pred is "deprecated"
-    display = RocCurveDisplay.from_predictions(
-        y_true, y_score=y_score, y_pred="deprecated"
-    )
-    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
-    assert_allclose(display.tpr, [0, 0, 1, 1])
-
 
+# TODO(1.9): remove
 def test_y_pred_deprecation_warning():
+    """Check that a warning is raised when y_pred is specified."""
     y_true = np.array([0, 1, 1, 0])
-    y_pred = np.array([0.1, 0.4, 0.35, 0.8])
+    y_score = np.array([0.1, 0.4, 0.35, 0.8])
 
-    with pytest.warns(FutureWarning, match="y_pred was deprecated in version 1.6"):
-        display = RocCurveDisplay.from_predictions(y_true, y_pred=y_pred)
+    with pytest.warns(FutureWarning, match="y_pred is deprecated in 1.7"):
+        display_y_pred = RocCurveDisplay.from_predictions(y_true, y_pred=y_score)
 
-    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
-    assert_allclose(display.tpr, [0, 0, 1, 1])
+    assert_allclose(display_y_pred.fpr, [0, 0.5, 0.5, 1])
+    assert_allclose(display_y_pred.tpr, [0, 0, 1, 1])
 
-    # Test that y_score is used when y_pred is "deprecated"
-    y_score = np.array([0.2, 0.3, 0.5, 0.1])
-    display = RocCurveDisplay.from_predictions(
-        y_true, y_score=y_score, y_pred="deprecated"
-    )
-    assert_allclose(display.fpr, [0, 0.5, 0.5, 1])
-    assert_allclose(display.tpr, [0, 0, 1, 1])
-    assert np.array_equal(display.y_score, y_score)
+    display_y_score = RocCurveDisplay.from_predictions(y_true, y_score)
+    assert_allclose(display_y_score.fpr, [0, 0.5, 0.5, 1])
+    assert_allclose(display_y_score.tpr, [0, 0, 1, 1])
 
 
 @pytest.mark.parametrize("despine", [True, False])

From f809813859fe1f7be29001ca66f456b862e60486 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 2 Jan 2025 14:31:16 +0100
Subject: [PATCH 11/14] remove tag changelog

---
 doc/whats_new/upcoming_changes/sklearn.metrics/29865.api.rst | 2 +-
 doc/whats_new/v1.6.rst                                       | 1 -
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/doc/whats_new/upcoming_changes/sklearn.metrics/29865.api.rst b/doc/whats_new/upcoming_changes/sklearn.metrics/29865.api.rst
index 8e171a1167b3a..60ea7d83de71f 100644
--- a/doc/whats_new/upcoming_changes/sklearn.metrics/29865.api.rst
+++ b/doc/whats_new/upcoming_changes/sklearn.metrics/29865.api.rst
@@ -1,4 +1,4 @@
-- |API| In :meth:`sklearn.metrics.RocCurveDisplay.from_predictions`,
+- In :meth:`sklearn.metrics.RocCurveDisplay.from_predictions`,
   the argument `y_pred` has been renamed to `y_score` to better reflect its purpose.
   `y_pred` will be removed in 1.9.
   By :user:`Bagus Tris Atmaja <bagustris>` in
diff --git a/doc/whats_new/v1.6.rst b/doc/whats_new/v1.6.rst
index 4a1c9e11a9892..47f8260820987 100644
--- a/doc/whats_new/v1.6.rst
+++ b/doc/whats_new/v1.6.rst
@@ -724,4 +724,3 @@ Søren Bredlund Caspersen, Stefanie Senger, Steffen Schneider, Štěpán
 Sršeň, Sylvain Combettes, Tamara, Thomas, Thomas Gessey-Jones, Thomas J. Fan,
 Thomas Li, Tialo, Tim Head, Tuhin Sharma, Tushar Parimi, vedpawar2254, Victoria
 Shevchenko, viktor765, Vince Carey, Virgil Chan, Wang Jiayi, Xiao Yuan, Xuefeng
-Xu, Yao Xiao, yareyaredesuyo, Zachary Vealey, Ziad Amerr

From 7721bb10c2a5ee11fb0012bfc5e2066fc3776d4b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?J=C3=A9r=C3=A9mie=20du=20Boisberranger?=
 <jeremie@probabl.ai>
Date: Sat, 12 Apr 2025 15:24:34 +0200
Subject: [PATCH 12/14] replace in examples + nitpicks

---
 .../plot_outlier_detection_bench.py           | 30 +++++++++----------
 sklearn/metrics/_plot/roc_curve.py            | 10 +++----
 2 files changed, 20 insertions(+), 20 deletions(-)

diff --git a/examples/miscellaneous/plot_outlier_detection_bench.py b/examples/miscellaneous/plot_outlier_detection_bench.py
index cef58e20d75eb..600eceb1a06b3 100644
--- a/examples/miscellaneous/plot_outlier_detection_bench.py
+++ b/examples/miscellaneous/plot_outlier_detection_bench.py
@@ -88,12 +88,12 @@ def fit_predict(estimator, X):
     tic = perf_counter()
     if estimator[-1].__class__.__name__ == "LocalOutlierFactor":
         estimator.fit(X)
-        y_pred = estimator[-1].negative_outlier_factor_
+        y_score = estimator[-1].negative_outlier_factor_
     else:  # "IsolationForest"
-        y_pred = estimator.fit(X).decision_function(X)
+        y_score = estimator.fit(X).decision_function(X)
     toc = perf_counter()
     print(f"Duration for {model_name}: {toc - tic:.2f} s")
-    return y_pred
+    return y_score
 
 
 # %%
@@ -138,7 +138,7 @@ def fit_predict(estimator, X):
 
 # %%
 y_true = {}
-y_pred = {"LOF": {}, "IForest": {}}
+y_score = {"LOF": {}, "IForest": {}}
 model_names = ["LOF", "IForest"]
 cat_columns = ["protocol_type", "service", "flag"]
 
@@ -150,7 +150,7 @@ def fit_predict(estimator, X):
         lof_kw={"n_neighbors": int(n_samples * anomaly_frac)},
         iforest_kw={"random_state": 42},
     )
-    y_pred[model_name]["KDDCup99 - SA"] = fit_predict(model, X)
+    y_score[model_name]["KDDCup99 - SA"] = fit_predict(model, X)
 
 # %%
 # Forest covertypes dataset
@@ -185,7 +185,7 @@ def fit_predict(estimator, X):
         lof_kw={"n_neighbors": int(n_samples * anomaly_frac)},
         iforest_kw={"random_state": 42},
     )
-    y_pred[model_name]["forestcover"] = fit_predict(model, X)
+    y_score[model_name]["forestcover"] = fit_predict(model, X)
 
 # %%
 # Ames Housing dataset
@@ -242,7 +242,7 @@ def fit_predict(estimator, X):
         lof_kw={"n_neighbors": int(n_samples * anomaly_frac)},
         iforest_kw={"random_state": 42},
     )
-    y_pred[model_name]["ames_housing"] = fit_predict(model, X)
+    y_score[model_name]["ames_housing"] = fit_predict(model, X)
 
 # %%
 # Cardiotocography dataset
@@ -271,7 +271,7 @@ def fit_predict(estimator, X):
         lof_kw={"n_neighbors": int(n_samples * anomaly_frac)},
         iforest_kw={"random_state": 42},
     )
-    y_pred[model_name]["cardiotocography"] = fit_predict(model, X)
+    y_score[model_name]["cardiotocography"] = fit_predict(model, X)
 
 # %%
 # Plot and interpret results
@@ -299,7 +299,7 @@ def fit_predict(estimator, X):
     for model_idx, model_name in enumerate(model_names):
         display = RocCurveDisplay.from_predictions(
             y_true[dataset_name],
-            y_pred[model_name][dataset_name],
+            y_score[model_name][dataset_name],
             pos_label=pos_label,
             name=model_name,
             ax=ax,
@@ -346,10 +346,10 @@ def fit_predict(estimator, X):
 for model_idx, (linestyle, n_neighbors) in enumerate(zip(linestyles, n_neighbors_list)):
     model.set_params(localoutlierfactor__n_neighbors=n_neighbors)
     model.fit(X)
-    y_pred = model[-1].negative_outlier_factor_
+    y_score = model[-1].negative_outlier_factor_
     display = RocCurveDisplay.from_predictions(
         y,
-        y_pred,
+        y_score,
         pos_label=pos_label,
         name=f"n_neighbors = {n_neighbors}",
         ax=ax,
@@ -386,10 +386,10 @@ def fit_predict(estimator, X):
 ):
     model = make_pipeline(preprocessor, lof)
     model.fit(X)
-    y_pred = model[-1].negative_outlier_factor_
+    y_score = model[-1].negative_outlier_factor_
     display = RocCurveDisplay.from_predictions(
         y,
-        y_pred,
+        y_score,
         pos_label=pos_label,
         name=str(preprocessor).split("(")[0],
         ax=ax,
@@ -438,10 +438,10 @@ def fit_predict(estimator, X):
 ):
     model = make_pipeline(preprocessor, lof)
     model.fit(X)
-    y_pred = model[-1].negative_outlier_factor_
+    y_score = model[-1].negative_outlier_factor_
     display = RocCurveDisplay.from_predictions(
         y,
-        y_pred,
+        y_score,
         pos_label=pos_label,
         name=str(preprocessor).split("(")[0],
         ax=ax,
diff --git a/sklearn/metrics/_plot/roc_curve.py b/sklearn/metrics/_plot/roc_curve.py
index ee3b5964f8b01..cc467296cfed1 100644
--- a/sklearn/metrics/_plot/roc_curve.py
+++ b/sklearn/metrics/_plot/roc_curve.py
@@ -358,7 +358,7 @@ def from_predictions(
             (as returned by “decision_function” on some classifiers).
 
             .. versionadded:: 1.7
-                `y_score` is now used instead of `y_pred`.
+                `y_pred` has been renamed to `y_score`.
 
         sample_weight : array-like of shape (n_samples,), default=None
             Sample weights.
@@ -437,15 +437,15 @@ def from_predictions(
         <...>
         >>> plt.show()
         """
-        # TODO(1.8): remove after the end of the deprecation period of `y_pred`
-        if y_score is not None and (
-            not isinstance(y_pred, str) or y_pred != "deprecated"
+        # TODO(1.9): remove after the end of the deprecation period of `y_pred`
+        if y_score is not None and not (
+            isinstance(y_pred, str) and y_pred == "deprecated"
         ):
             raise ValueError(
                 "`y_pred` and `y_score` cannot be both specified. Please use `y_score`"
                 " only as `y_pred` is deprecated in 1.7 and will be removed in 1.9."
             )
-        if not isinstance(y_pred, str) or y_pred != "deprecated":
+        if not (isinstance(y_pred, str) and y_pred == "deprecated"):
             warnings.warn(
                 (
                     "y_pred is deprecated in 1.7 and will be removed in 1.9. "

From fc8df122c316cff481ed46c40fa75cbc08f0583e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?J=C3=A9r=C3=A9mie=20du=20Boisberranger?=
 <jeremie@probabl.ai>
Date: Sat, 12 Apr 2025 15:25:17 +0200
Subject: [PATCH 13/14] [doc build]


From 4435e091ad4f8420997b0adf58d77a8cdedc13e8 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?J=C3=A9r=C3=A9mie=20du=20Boisberranger?=
 <jeremie@probabl.ai>
Date: Sat, 12 Apr 2025 16:01:23 +0200
Subject: [PATCH 14/14] iter [doc build] [azure parallel]

---
 sklearn/metrics/_plot/tests/test_roc_curve_display.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/metrics/_plot/tests/test_roc_curve_display.py b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
index 93ef019a51602..c2e6c865fa9a9 100644
--- a/sklearn/metrics/_plot/tests/test_roc_curve_display.py
+++ b/sklearn/metrics/_plot/tests/test_roc_curve_display.py
@@ -365,7 +365,7 @@ def test_y_score_and_y_pred_specified_error():
 
 
 # TODO(1.9): remove
-def test_y_pred_deprecation_warning():
+def test_y_pred_deprecation_warning(pyplot):
     """Check that a warning is raised when y_pred is specified."""
     y_true = np.array([0, 1, 1, 0])
     y_score = np.array([0.1, 0.4, 0.35, 0.8])