title: How to set custom stop words for sklearn CountVectorizer?
body: <p>I'm trying to run LDA (Latent Dirichlet Allocation) on a non-English text dataset.</p>
  
  <p>From sklearn's tutorial, there's this part where you count term frequency of the words to feed into the LDA:</p>
  
  <pre><code>tf_vectorizer = CountVectorizer(max_df=0.95, min_df=2,
                              max_features=n_features,
                              stop_words='english')
  </code></pre>
  
  <p>Which has built-in stop words feature which is only available for English I think. How could I use my own stop words list for this?</p>