title: How to adjust alpha parameter in gensim LdaModel
body: <p>I have trained an topic model using a symmetric alpha in my lda distibution:</p>
  
  <pre><code>model = gensim.models.ldamodel.LdaModel(bows, num_topics = 20, id2word = dictionary, passes = 100)
  </code></pre>
  
  <p>I can see that:</p>
  
  <pre><code>model.alpha
  array([ 0.05,  0.05,  0.05,  0.05,  0.05,  0.05,  0.05,  0.05,  0.05,
      0.05,  0.05,  0.05,  0.05,  0.05,  0.05,  0.05,  0.05,  0.05,
      0.05,  0.05])
  </code></pre>
  
  <p>where </p>
  
  <pre><code>numpy.sum(model.alpha)
  1.0000000000000002
  </code></pre>
  
  <p>I can't quite understand how gensim allows for lowering alpha parameter to allow each document to be a mixture of fewer topics?</p>