title: CountVectorizer(): StreamBackedCorpusView' object has no attribute 'lower'
body: <p>I am trying to run and instantiate CountVectorizer() on NLTK Movie reviews corpus, using the following code:</p>
  
  <pre><code>&gt;&gt;&gt;import nltk
  &gt;&gt;&gt;import nltk.corpus
  &gt;&gt;&gt;from sklearn.feature_extraction.text import CountVectorizer
  &gt;&gt;&gt;from nltk.corpus import movie_reviews
  &gt;&gt;&gt;neg_rev = movie_reviews.fileids('neg')
  &gt;&gt;&gt;pos_rev = movie_reviews.fileids('pos')
  &gt;&gt;&gt;rev_list = [] # Empty List
  &gt;&gt;&gt;for rev in neg_rev:
      rev_list.append(nltk.corpus.movie_reviews.words(rev))
  &gt;&gt;&gt;for rev_pos in pos_rev:
      rev_list.append(nltk.corpus.movie_reviews.words(rev_pos))
  &gt;&gt;&gt;count_vect = CountVectorizer()
  &gt;&gt;&gt;X_count_vect = count_vect.fit_transform(rev_list)
  </code></pre>
  
  <p>I am getting the following error:</p>
  
  <pre><code>AttributeError                            Traceback (most recent call last)
  &lt;ipython-input-37-00e9047daa67&gt; in &lt;module&gt;()
  ----&gt; 1 X_count_vect = count_vect.fit_transform(rev_list)
  
  C:\ProgramData\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in fit_transform(self, raw_documents, y)
      837 
      838         vocabulary, X = self._count_vocab(raw_documents,
  --&gt; 839                                           self.fixed_vocabulary_)
      840 
      841         if self.binary:
  
  C:\ProgramData\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in _count_vocab(self, raw_documents, fixed_vocab)
      760         for doc in raw_documents:
      761             feature_counter = {}
  --&gt; 762             for feature in analyze(doc):
      763                 try:
      764                     feature_idx = vocabulary[feature]
  
  C:\ProgramData\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in &lt;lambda&gt;(doc)
      239 
      240             return lambda doc: self._word_ngrams(
  --&gt; 241                 tokenize(preprocess(self.decode(doc))), stop_words)
      242 
      243         else:
  
  C:\ProgramData\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in &lt;lambda&gt;(x)
      205 
      206         if self.lowercase:
  --&gt; 207             return lambda x: strip_accents(x.lower())
      208         else:
      209             return strip_accents
  
  AttributeError: 'StreamBackedCorpusView' object has no attribute 'lower'
  </code></pre>
  
  <p><code>nltk.corpus.movie_reviews.words(rev_pos)</code> has tokenized sentences.... such as:</p>
  
  <pre><code>['films', 'adapted', 'from', 'comic', 'books', 'have', ...]
  </code></pre>
  
  <p>Can anyone please tell me what am I doing wrong? I Suppose I am miising some tstep in creating the list of <code>(rev_list)</code> of movie reviews.</p>
  
  <p>TIA</p>