tentative fix for #649

Author: yzhao062

CHANGES.txt

@@ -199,4 +199,7 @@ v<2.0.2>, <07/06/2024> -- Complete of removing all Tensorflow and Keras code.
 v<2.0.2>, <07/21/2024> -- Add DevNet.
 v<2.0.3>, <09/06/2024> -- Add Reject Option in Unsupervised Anomaly Detection (#605).
 v<2.0.3>, <12/20/2024> -- Massive documentation polish.
-v<2.0.5>, <09/04/2025> -- Finally, add the auto model selector (#616).
+v<2.0.4>, <04/29/2025> -- Mistakenly we skipped 2.0.4.
+v<2.0.5>, <04/29/2025> -- Add wheel for better installation.
+v<2.0.6>, <09/04/2025> -- Finally, add the auto model selector (#616).
+v<2.0.6>, <12/01/2025> -- Pre-caution for new sklearn break change(#649).

pyod/models/base.py

@@ -14,6 +14,7 @@
 from numpy import percentile
 from scipy.special import erf
 from scipy.stats import binom
+from sklearn.base import BaseEstimator
 from sklearn.metrics import roc_auc_score
 from sklearn.preprocessing import MinMaxScaler
 from sklearn.utils import deprecated
@@ -25,7 +26,7 @@
 from ..utils.utility import precision_n_scores
 
 
-class BaseDetector(metaclass=abc.ABCMeta):
+class BaseDetector(BaseEstimator, metaclass=abc.ABCMeta):
     """Abstract class for all outlier detection algorithms.
 
 
@@ -711,3 +712,16 @@ def __repr__(self):
         class_name = self.__class__.__name__
         return '%s(%s)' % (class_name, _pprint(self.get_params(deep=False),
                                                offset=len(class_name), ),)
+
+
+    def __sklearn_tags__(self):
+        """Return sklearn-style Tags for compatibility with scikit-learn >= 1.8.
+
+        We mark all PyOD detectors as 'outlier_detector' so that utilities
+        such as sklearn.utils._tags.get_tags and is_outlier_detector work.
+        """
+        tags = super().__sklearn_tags__()
+        # match sklearn's OutlierMixin
+        tags.estimator_type = "outlier_detector"
+        return tags
+

pyod/test/test_base.py

@@ -15,6 +15,14 @@
 from pyod.models.base import BaseDetector
 from pyod.utils.data import generate_data
 
+from sklearn.utils.validation import check_is_fitted
+
+try:
+    # Present in newer sklearn versions (1.3+, 1.4+, 1.8rc1, etc.)
+    from sklearn.utils._tags import get_tags
+except ImportError:
+    get_tags = None
+
 
 # Check sklearn\tests\test_base
 # A few test classes
@@ -207,6 +215,24 @@ def test_get_params(self):
     def tearDown(self):
         pass
 
+    @unittest.skipIf(get_tags is None, "sklearn is too old and does not provide get_tags")
+    def test_sklearn_tags_and_check_is_fitted(self):
+        # Dummy1 is a BaseDetector subclass
+        clf = Dummy1()
+
+        # 1. get_tags should work and identify it as outlier_detector
+        tags = get_tags(clf)
+        assert_equal(tags.estimator_type, "outlier_detector")
+
+        # 2. Simulate a fitted model
+        clf.labels_ = np.zeros(10)
+        clf.decision_scores_ = np.zeros(10)
+        clf.threshold_ = 0.5
+
+        # This should NOT raise AttributeError on sklearn >= 1.8
+        check_is_fitted(clf, ['decision_scores_', 'threshold_', 'labels_'])
+
+
 
 if __name__ == '__main__':
     unittest.main()