title: Error while selecting important features in MultinomialNB
body: <p>The following is my code:</p>
  
  <pre><code>feature_names1 = np.hstack([text_bow_train,title_bow_train,X_train_cat_ohe,X_train_subcat_ohe, X_train_state_ohe, X_train_pre_ohe, X_train_grade_ohe, "Price","Number of Previously posted project","Quantity"])
  
  def most_important_features(vectorizer, classifier, n=5):
      class_labels = classifier.classes_
      feature_names = vectorizer.get_feature_names()
      topn_class1 = sorted(zip(classifier.coef_[0], feature_names))[:n]
      topn_class2 = sorted(zip(classifier.coef_[0], feature_names))[-n:]
  
      for coef, feat in topn_class1:
          print(class_labels[0], coef, feat)
  
      for coef, feat in reversed(topn_class2):
          print(class_labels[1], coef, feat)
  
  
  most_important_features(feature_names1, mnb)
  </code></pre>
  
  <p>I am getting the following error:  </p>
  
  <blockquote>
    <p>AttributeError: 'numpy.ndarray' object has no attribute 'get_feature_names'</p>
  </blockquote>