title: What does the parameter "mds" mean in the pyLDAvis.sklearn.prepare () - function?
body: <p>I want to visualize the topic modeling made with the LDA-algorithm. I use the python module called &quot;pyldavis&quot; and as environment the jupyter notebook.</p>
  <pre><code>import pyLDAvis.sklearn
  ...
  pyLDAvis.sklearn.prepare(lda_tf, dtm_tf, tf_vectorizer)
  pyLDAvis.sklearn.prepare(lda_tf, dtm_tf, tf_vectorizer, mds='mmds')
  pyLDAvis.sklearn.prepare(lda_tf, dtm_tf, tf_vectorizer, mds='tsne')
  </code></pre>
  <p>It does work fine, but I don't really understand the mds-parameter... Even after reading the documentation:</p>
  <blockquote>
  <p>mds :function or a string representation of function</p>
  <p>A function that takes topic_term_dists as an input and outputs a n_topics by 2 distance matrix. The output approximates the distance between topics. See js_PCoA() for details on the default function. A string representation currently accepts pcoa (or upper case variant), mmds (or upper case variant) and tsne (or upper case variant), if sklearn package is installed for the latter two.</p>
  </blockquote>
  <p>Does somebody know what the differences btw. mds='pcoa', mds='mmds', mds='tsne'?</p>
  <p>Thanks!</p>