From b2eace8555403adf4a10630f3c66a31ea974c897 Mon Sep 17 00:00:00 2001
From: pedrobslima <pedrobslima2003@gmail.com>
Date: Sun, 14 Dec 2025 14:19:03 -0300
Subject: [PATCH] Compatibility with sklearn 1.7: Update data validation
 function during fit

Models couldn't be trained because BaseEstimator._validate_data() is deprecated since sklearn version 1.7, and needed to be switched to sklearn.utils.validation.validate_data()
---
 deslib/base.py                    | 5 +++--
 deslib/static/oracle.py           | 5 +++--
 deslib/static/single_best.py      | 5 +++--
 deslib/static/stacked.py          | 5 +++--
 deslib/static/static_selection.py | 5 +++--
 5 files changed, 15 insertions(+), 10 deletions(-)

diff --git a/deslib/base.py b/deslib/base.py
index c3f1841..5091eea 100644
--- a/deslib/base.py
+++ b/deslib/base.py
@@ -18,7 +18,7 @@
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.preprocessing import LabelEncoder, normalize
 from sklearn.utils.validation import (check_X_y, check_is_fitted, check_array,
-                                      check_random_state)
+                                      check_random_state, validate_data)
 
 from deslib.util import KNNE
 from deslib.util import faiss_knn_wrapper
@@ -83,7 +83,8 @@ class labels of each example in X.
         self
         """
         self.random_state_ = check_random_state(self.random_state)
-        X, y = self._validate_data(
+        X, y = validate_data(
+            self,
             X,
             y,
             accept_sparse="csr",
diff --git a/deslib/static/oracle.py b/deslib/static/oracle.py
index d1d7662..b213d4d 100644
--- a/deslib/static/oracle.py
+++ b/deslib/static/oracle.py
@@ -5,7 +5,7 @@
 # License: BSD 3 clause
 
 import numpy as np
-from sklearn.utils.validation import check_X_y, check_array
+from sklearn.utils.validation import check_X_y, check_array, validate_data
 
 from deslib.static.base import BaseStaticEnsemble
 
@@ -68,7 +68,8 @@ class labels of each example in X.
         self : object
             Returns self.
         """
-        X, y = self._validate_data(
+        X, y = validate_data(
+            self,
             X,
             y,
             accept_sparse="csr",
diff --git a/deslib/static/single_best.py b/deslib/static/single_best.py
index 6edb5c1..6f2ad35 100644
--- a/deslib/static/single_best.py
+++ b/deslib/static/single_best.py
@@ -6,7 +6,7 @@
 
 import numpy as np
 from sklearn.metrics import check_scoring
-from sklearn.utils.validation import check_X_y, check_is_fitted, check_array
+from sklearn.utils.validation import check_X_y, check_is_fitted, check_array, validate_data
 
 from .base import BaseStaticEnsemble
 
@@ -74,7 +74,8 @@ def fit(self, X, y):
             class labels of each example in X.
 
         """
-        X, y = self._validate_data(
+        X, y = validate_data(
+            self,
             X,
             y,
             accept_sparse="csr",
diff --git a/deslib/static/stacked.py b/deslib/static/stacked.py
index f24b22e..23e6686 100644
--- a/deslib/static/stacked.py
+++ b/deslib/static/stacked.py
@@ -1,6 +1,6 @@
 import numpy as np
 from sklearn.linear_model import LogisticRegression
-from sklearn.utils.validation import check_X_y, check_array, check_is_fitted
+from sklearn.utils.validation import check_X_y, check_array, check_is_fitted, validate_data
 
 from deslib.static.base import BaseStaticEnsemble
 
@@ -70,7 +70,8 @@ def fit(self, X, y):
             class labels of each example in X.
 
         """
-        X, y = self._validate_data(
+        X, y = validate_data(
+            self,
             X,
             y,
             accept_sparse="csr",
diff --git a/deslib/static/static_selection.py b/deslib/static/static_selection.py
index cc0ef95..44b7889 100644
--- a/deslib/static/static_selection.py
+++ b/deslib/static/static_selection.py
@@ -6,7 +6,7 @@
 
 import numpy as np
 from sklearn.metrics import check_scoring
-from sklearn.utils.validation import check_is_fitted, check_X_y, check_array
+from sklearn.utils.validation import check_is_fitted, check_X_y, check_array, validate_data
 
 from deslib.util.aggregation import majority_voting_rule
 from deslib.util.aggregation import predict_proba_ensemble
@@ -86,7 +86,8 @@ class labels of each example in X.
         self : object
             Returns self.
         """
-        X, y = self._validate_data(
+        X, y = validate_data(
+            self,
             X,
             y,
             accept_sparse="csr",