mlxtend: drop redundant patch+test skips

From 1fb59eb42f4bef229b953de313c7e78f0857ea42 Mon Sep 17 00:00:00 2001

From: Philip Wilk <p.wilk@student.reading.ac.uk>

Date: Sun, 23 Mar 2025 16:14:51 +0000

Subject: [PATCH] StackingCVClassifier/fit: ensure compatibility with

 *scikit-learn* versions 1.4 and above by dynamically selecting between

 `fit_params` and `params`

---

 mlxtend/classifier/stacking_cv_classification.py | 5 ++++-

 mlxtend/regressor/stacking_cv_regression.py      | 6 +++++-

 2 files changed, 9 insertions(+), 2 deletions(-)

diff --git a/mlxtend/classifier/stacking_cv_classification.py b/mlxtend/classifier/stacking_cv_classification.py

index 5bff6907..f4c45b8c 100644

--- a/mlxtend/classifier/stacking_cv_classification.py

+++ b/mlxtend/classifier/stacking_cv_classification.py

@@ -15,6 +15,7 @@ from sklearn.base import TransformerMixin, clone

 from sklearn.model_selection import cross_val_predict

 from sklearn.model_selection._split import check_cv

 from sklearn.preprocessing import LabelEncoder

+from sklearn import __version__ as sklearn_version

 from ..externals.estimator_checks import check_is_fitted

 from ..externals.name_estimators import _name_estimators

@@ -266,6 +267,8 @@ class StackingCVClassifier(

             if self.verbose > 1:

                 print(_name_estimators((model,))[0][1])

+            param_name = "fit_params" if sklearn_version < "1.4" else "params"

+

             prediction = cross_val_predict(

                 model,

                 X,

@@ -273,10 +276,10 @@ class StackingCVClassifier(

                 groups=groups,

                 cv=final_cv,

                 n_jobs=self.n_jobs,

-                fit_params=fit_params,

                 verbose=self.verbose,

                 pre_dispatch=self.pre_dispatch,

                 method="predict_proba" if self.use_probas else "predict",

+                **{param_name: fit_params},

             )

             if not self.use_probas:

diff --git a/mlxtend/regressor/stacking_cv_regression.py b/mlxtend/regressor/stacking_cv_regression.py

index a1faf2ff..d2fb1c49 100644

--- a/mlxtend/regressor/stacking_cv_regression.py

+++ b/mlxtend/regressor/stacking_cv_regression.py

@@ -19,6 +19,7 @@ from sklearn.base import RegressorMixin, TransformerMixin, clone

 from sklearn.model_selection import cross_val_predict

 from sklearn.model_selection._split import check_cv

 from sklearn.utils import check_X_y

+from sklearn import __version__ as sklearn_version

 from ..externals.estimator_checks import check_is_fitted

 from ..externals.name_estimators import _name_estimators

@@ -211,6 +212,9 @@ class StackingCVRegressor(_BaseXComposition, RegressorMixin, TransformerMixin):

             fit_params = None

         else:

             fit_params = dict(sample_weight=sample_weight)

+

+        param_name = "fit_params" if sklearn_version < "1.4" else "params"

+

         meta_features = np.column_stack(

             [

                 cross_val_predict(

@@ -221,8 +225,8 @@ class StackingCVRegressor(_BaseXComposition, RegressorMixin, TransformerMixin):

                     cv=kfold,

                     verbose=self.verbose,

                     n_jobs=self.n_jobs,

-                    fit_params=fit_params,

                     pre_dispatch=self.pre_dispatch,

+                    **{param_name: fit_params},

                 )

                 for regr in self.regr_

             ]

-- 

2.47.1

    joblib

  ];

  patches = [

    # https://github.com/rasbt/mlxtend/issues/1117

    ./0001-StackingCVClassifier-fit-ensure-compatibility-with-s.patch

  ];

  nativeCheckInputs = [ pytestCheckHook ];

  pytestFlags = [ "-sv" ];

    "mlxtend/evaluate/tests/test_feature_importance.py" # urlopen error

    "mlxtend/evaluate/tests/test_bias_variance_decomp.py" # keras.api._v2

    "mlxtend/evaluate/tests/test_bootstrap_point632.py" # keras.api._v2

    # Failing tests, most likely an upstream issue. See https://github.com/rasbt/mlxtend/issues/1117

    "mlxtend/classifier/tests/test_ensemble_vote_classifier.py"

    "mlxtend/classifier/tests/test_stacking_classifier.py"

    "mlxtend/classifier/tests/test_stacking_cv_classifier.py"

  ];

  meta = {