fix

Author: glemaitre

imblearn/base.py

@@ -300,16 +300,16 @@ def fit_resample(self, X, y):
 
             if self._y_name is not None:
                 y_ = pd.Series(y_, dtype=self._y_dtype, name=self._y_name)
+
+            if binarize_y:
+                if len(output) == 2:
+                    return X_, y_
+                return X_, y_, output[2]
         else:
             X_, y_ = output[0], output[1]
-
-        if binarize_y:
             if len(output) == 2:
                 return X_, y_
             return X_, y_, output[2]
-        if len(output) == 2:
-            return X_, y_
-        return X_, y_, output[2]
 
     def _fit_resample(self, X, y):
         func = _identity if self.func is None else self.func

imblearn/over_sampling/_smote.py

@@ -892,8 +892,22 @@ def _check_X_y(self, X, y):
         """Overwrite the checking to let pass some string for categorical
         features.
         """
-        # store the columns name to reconstruct a dataframe
-        self._columns = X.columns if hasattr(X, "loc") else None
+        if hasattr(X, "loc"):
+            # store information to build dataframe
+            self._X_columns = X.columns
+            self._X_dtypes = X.dtypes
+        else:
+            self._X_columns = None
+            self._X_dtypes = None
+
+        if hasattr(y, "loc"):
+            # store information to build a series
+            self._y_name = y.name
+            self._y_dtype = y.dtype
+        else:
+            self._y_name = None
+            self._y_dtype = None
+
         y, binarize_y = check_target_type(y, indicate_one_vs_all=True)
         X, y = check_X_y(X, y, accept_sparse=["csr", "csc"], dtype=None)
         return X, y, binarize_y