Define _estimator_has()

eli5/lime/utils.py

@@ -12,6 +12,11 @@
 from eli5.utils import vstack
 from eli5.sklearn.utils import sklearn_version
 
+def _estimator_has(attr):
+ def check(self):
+ return hasattr(self.estimator, attr)
+
+ return check
 
 def fit_proba(clf, X, y_proba, expand_factor=10, sample_weight=None,
  shuffle=True, random_state=None,

eli5/sklearn/permutation_importance.py

@@ -17,6 +17,12 @@
 from eli5.permutation_importance import get_score_importances
 from eli5.sklearn.utils import pandas_available
 
+def _estimator_has(attr):
+ def check(self):
+ return hasattr(self.estimator, attr)
+
+ return check
+
 if pandas_available:
  import pandas as pd