text: Title: Bug in _partial_fit_and_predict_iterative in train_evaluator.py?
  Body: Hi, 
  
  Working with [AutoSklearn2Classifier](https://github.com/automl/auto-sklearn/blob/b2ac331c500ebef7becf372802493a7b235f7cec/autosklearn/experimental/askl2.py#L180), I recently got a strange error that might be due to a bug. This is what I am running:
  
  ```python
      n_cores = 10
      memory_limit= psutil.virtual_memory().available * 10**-6 // n_cores
      time_left_for_this_task = 7200
  
      predictor = AutoSklearn2Classifier(memory_limit=memory_limit,
                                         metric=autosklearn_metrics.roc_auc,
                                         n_jobs=n_cores,
                                         time_left_for_this_task=time_left_for_this_task
                                        )
  
      predictor.fit(x_train, y_train)
      predictor.automl_.runhistory_.data
  ```
  
  where `x_train` is a pandas dataframe and `y_train` a list. Even though `fit` runs, after inspecting `runhistory_.data` it is clear that all models are crashing in line 741 of /autosklearn/evaluation/train_evaluator.py. It seems like `self.Y_train` in line 741 should be `self.X_train` instead:
  
  https://github.com/automl/auto-sklearn/blob/b2ac331c500ebef7becf372802493a7b235f7cec/autosklearn/evaluation/train_evaluator.py#L738-L744
  
  I found that a workaround for this issue is providing `x_train` as numpy. Also tried providing `x_train` as a list of lists or `y_train` as pandas series, but neither of them solved the issue. I am using auto-sklearn==0.14.7.
  
  I am wondering if this is the expected behavior or actually a bug. Thanks!