Fix AttributeError issue when verbose > 1 in StackingClassifier

rasbt · Jul 21, 2016 · a22f3d5 · a22f3d5
1 parent 31e75d2
commit a22f3d5
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Showing 3 changed files with 14 additions and 1 deletion.
diff --git a/docs/sources/CHANGELOG.md b/docs/sources/CHANGELOG.md
@@ -25,6 +25,7 @@ imput arrays via `transform` and `fit_transform`
 - More rigorous type and shape checks in `evaluate.plot_decision_regions`
 - Changes in `DenseTransformer` so that it doesn't fail if the input array is not sparse
 - Use scikit-learn's `BaseEstimator` as parent class for `feature_selection.ColumnSelector`
+- Fix `AttributeError` issue when `verbose` > 1 in `StackingClassifier`
 
 ### Version 0.4.1 (2016-05-01)
 

diff --git a/mlxtend/classifier/stacking_classification.py b/mlxtend/classifier/stacking_classification.py
@@ -93,7 +93,7 @@ def fit(self, X, y):
             if self.verbose > 0:
                 i = self.clfs_.index(clf) + 1
                 print("Fitting classifier%d: %s (%d/%d)" %
-                      (i, _name_estimators((clf,))[0][0], i, len(self.clf_)))
+                      (i, _name_estimators((clf,))[0][0], i, len(self.clfs_)))
 
             if self.verbose > 2:
                 if hasattr(clf, 'verbose'):

diff --git a/mlxtend/classifier/tests/test_stacking_classifier.py b/mlxtend/classifier/tests/test_stacking_classifier.py
@@ -131,3 +131,15 @@ def test_not_fitted():
                   " before using this method.",
                   sclf.predict_proba,
                   iris.data)
+
+
+def test_verbose():
+    np.random.seed(123)
+    meta = LogisticRegression()
+    clf1 = RandomForestClassifier()
+    clf2 = GaussianNB()
+    sclf = StackingClassifier(classifiers=[clf1, clf2],
+                              use_probas=True,
+                              meta_classifier=meta,
+                              verbose=3)
+    sclf.fit(iris.data, iris.target)