title: CountVectorizer converts words to lower case
body: <p>In my classification model, I need to maintain uppercase letters, but when I use sklearn countVectorizer to built the vocabulary, uppercase letters convert to lowercase!</p>
  
  <p>To exclude implicit tokinization, I built a tokenizer which just pass the text without any operation ..</p>
  
  <p>my code:</p>
  
  <pre><code>co = dict()
  
  def tokenizeManu(txt):
      return txt.split()
  
  def corpDict(x):
      print('1: ', x)
      count = CountVectorizer(ngram_range=(1, 1), tokenizer=tokenizeManu)
      countFit = count.fit_transform(x)
      vocab = count.get_feature_names()
      dist = np.sum(countFit.toarray(), axis=0)
      for tag, count in zip(vocab, dist):
          co[str(tag)] = count
  
  x = ['I\'m John Dev', 'We are the only']
  
  corpDict(x)
  print(co)
  </code></pre>
  
  <p>the output:</p>
  
  <pre><code>1:  ["I'm John Dev", 'We are the only'] #&lt;- before building the vocab.
  {'john': 1, 'the': 1, 'we': 1, 'only': 1, 'dev': 1, "i'm": 1, 'are': 1} #&lt;- after
  </code></pre>